What is the difference between a distributed ledger and a traditional ledger?

The core difference between a distributed ledger technology (DLT) and a traditional ledger lies in decentralization. Traditional ledgers, like those used by banks, are centralized. This means a single entity (the bank) controls and manages the entire ledger. All transactions are recorded and verified by this central authority.

DLT, on the other hand, operates on a peer-to-peer (P2P) network. Think of it as a shared, replicated database spread across many computers. Multiple nodes (computers) simultaneously store, validate, and update the ledger. This distributed nature offers several key advantages:

Increased Transparency and Security: Because the ledger is replicated across many nodes, it’s incredibly difficult to alter or tamper with the data. Any attempt to do so would be immediately detected by other nodes.
Enhanced Resilience: There’s no single point of failure. Even if some nodes go offline, the ledger remains operational and accessible.
Improved Efficiency: The distributed validation process speeds up transactions and reduces reliance on intermediaries.
Greater Trust: Decentralization fosters trust because no single entity controls the data. All participants have a copy of the ledger and can independently verify its integrity.

Here’s a simple analogy: imagine a shared Google Doc. Multiple people can access, edit, and see the changes in real-time. A traditional ledger is like a single, locked notebook only accessible to one person. The differences are significant.

Different types of DLTs exist, each with its own unique characteristics. For example, blockchain is a specific type of DLT that uses blocks of data linked cryptographically to ensure immutability. Other DLTs may employ different consensus mechanisms and data structures.

Public Blockchains: Completely open and accessible to anyone, like Bitcoin.
Private Blockchains: Permissioned networks with controlled access, suitable for enterprise use.
Consortium Blockchains: Shared by a group of organizations, balancing privacy and transparency.

Understanding the fundamental differences between DLT and traditional ledgers is crucial to grasping the potential of blockchain and other emerging crypto technologies.

What is a distributed ledger system?

A distributed ledger system (DLS) is essentially a database replicated across multiple participants in a network. Instead of a single central authority controlling the data, each participant holds a complete or partial copy of the ledger. This shared, synchronized database records transactions, providing transparency and immutability.

Key features that distinguish DLS from traditional databases include:

Decentralization: No single entity controls the system, reducing the risk of censorship or single points of failure.
Transparency: All participants can view the transaction history, enhancing accountability and trust.
Immutability: Once a transaction is recorded, it cannot be altered or deleted, ensuring data integrity.
Security: Cryptographic hashing and consensus mechanisms protect the ledger from unauthorized modifications.

Different types of DLS exist, each using various consensus mechanisms to validate and add new blocks of transactions to the ledger. Popular examples include:

Blockchain: A chain of blocks, each containing a batch of transactions, linked cryptographically. Bitcoin and Ethereum utilize this technology.
Hashgraph: A directed acyclic graph (DAG) that provides faster transaction processing compared to blockchain.
Directed Acyclic Graph (DAG): A more flexible structure than blockchain, allowing for parallel transaction processing. IOTA is a notable example.

Consensus mechanisms ensure that all participants agree on the valid state of the ledger. These mechanisms, like Proof-of-Work (PoW), Proof-of-Stake (PoS), and Practical Byzantine Fault Tolerance (PBFT), are crucial for the security and integrity of the DLS. The choice of consensus mechanism significantly impacts the system’s performance and security trade-offs.

Applications of DLS extend beyond cryptocurrencies: They are increasingly used in supply chain management, voting systems, healthcare records, digital identity verification, and more, offering solutions for improved transparency, security, and trust in various industries.

What is the difference between Merkle tree and Merkle Dag?

Merkle trees and Merkle Directed Acyclic Graphs (DAGs) are both crucial data structures in cryptography, particularly in distributed ledger technologies like blockchain. However, they differ significantly in their structure and capabilities.

Merkle trees are hierarchical structures where each non-leaf node is the hash of its children. This ensures data integrity; any change in the underlying data will propagate up the tree, altering the root hash. The balanced nature of the tree – each node having either zero or two children – is essential for its efficient computation.

Merkle DAGs, on the other hand, relax this balanced requirement. They maintain the hashing principle – each node is a hash of its children – but allow for a more flexible structure. Nodes can have multiple parents, resulting in a directed acyclic graph instead of a tree. This increased flexibility is key. It allows for more complex data relationships to be represented.

This lack of balance and the ability to have multiple parents translates into significant advantages. First, Merkle DAGs can efficiently represent data with complex dependencies. Think of version control systems like Git: each commit builds upon previous ones, and a Merkle DAG perfectly captures this history. Second, Merkle DAGs are more space-efficient in certain scenarios. Because they avoid the need for padding to maintain a balanced tree structure, they can be more compact when representing data with uneven branching.

Furthermore, every node in a Merkle DAG can carry a payload. This payload can be any data, allowing for richer information storage than a Merkle tree where nodes essentially just store hashes. This makes them suitable for applications needing to store and verify large amounts of data efficiently.

In essence, a Merkle tree is a special case of a Merkle DAG – a highly structured and balanced one. Choosing between them depends on the specific application’s needs. If a balanced, simple structure suffices, a Merkle tree might be preferable. If flexibility, efficient handling of complex data relationships, and payload storage are required, a Merkle DAG is the more suitable choice.

What is the difference between Merkle tree and blockchain?

Think of a Merkle tree as a super-efficient summary of all the transactions in a blockchain block. It’s like a highly organized index. Instead of having to check every single transaction (potentially thousands in a Bitcoin block, which can hold around 1MB of data), you only need to verify the root hash of the Merkle tree. This root hash is included in the block header, acting as a digital fingerprint for the entire block’s transactions.

Each transaction gets its own unique hash (a cryptographic fingerprint). These hashes are paired and hashed together repeatedly until you reach a single root hash at the top of the Merkle tree. If even one transaction is altered, its hash changes, propagating the change up the tree and resulting in a different root hash. This makes the system incredibly secure and tamper-proof.

The blockchain itself is a chain of blocks, where each block contains the Merkle root, along with other metadata like timestamps and the previous block’s hash. The Merkle tree is therefore integral to the blockchain’s integrity and efficiency. It allows for quick verification of data integrity without having to download and process the entire block’s transaction data. This is crucial for scalability and fast transaction confirmation times.

Essentially, the Merkle tree is a core component enabling the blockchain to function efficiently and securely – a vital piece of the puzzle for cryptocurrencies like Bitcoin.

What is the relationship between blockchain and distributed ledger technology?

Blockchain and distributed ledger technology (DLT) are intrinsically linked, but not synonymous. DLT is a broader concept encompassing any database replicated and synchronized across multiple participants. This shared, auditable record uses cryptographic methods for integrity and verification, potentially residing on decentralized or centralized networks. Crucially, consensus mechanisms are employed to ensure data consistency across all nodes – examples include Proof-of-Work (PoW), Proof-of-Stake (PoS), and Practical Byzantine Fault Tolerance (PBFT).

Blockchain is a specific *implementation* of DLT. It achieves consensus through chained blocks of data, each cryptographically linked to the previous one. This linear, append-only structure creates an immutable, tamper-evident history. While blockchains excel at ensuring data integrity and transparency, they can face scalability challenges, particularly with high transaction volumes. The inherent sequential processing of blocks can lead to latency issues. Furthermore, not all DLTs need a block structure; some use different data structures and consensus algorithms, such as directed acyclic graphs (DAGs) in IOTA or Hashgraph in Hedera Hashgraph, which offer alternative approaches to achieving distributed consensus and enhanced scalability.

Therefore, while every blockchain is a form of DLT, the converse isn’t true. Many other DLT systems exist, each with unique properties and trade-offs, potentially better suited for specific applications beyond cryptocurrency, such as supply chain management, voting systems, and digital identity. The choice between a blockchain-based DLT and an alternative depends heavily on the desired level of decentralization, security, performance requirements, and the specific application needs.

What is the difference between distributed ledger and centralized ledger?

Imagine a giant notebook. A centralized ledger is like that notebook being kept by one person – a bank, for example. They control everything: who can write in it, what they write, and when. Only they can make changes. This is how traditional banking works.

A decentralized ledger, like a blockchain, is different. It’s like that notebook being shared among many people. Nobody owns it alone. Everyone has a copy, and any change needs agreement from many people before it’s added. This makes it much harder to cheat or change things secretly.

Centralized Ledger:
Single point of control (e.g., a bank).
High risk of single point of failure.
Easier to manipulate.
Transactions are processed faster.
Decentralized Ledger:
Distributed control (many participants).
More resistant to manipulation and censorship.
Increased security through redundancy.
Transactions can be slower due to consensus mechanisms.

Think of it this way: a centralized system is like a single, powerful king ruling a kingdom, while a decentralized system is more like a democracy where decisions are made collectively.

Here’s an interesting point: The decentralized nature of blockchains improves transparency. Since everyone has a copy of the ledger, everyone can see the transactions. However, individual identities are usually not visible for privacy reasons, unless intentionally shared.

What is the difference between the two types of the ledger?

The core distinction lies between the general ledger and subsidiary ledgers. Think of the general ledger as the ultimate, all-encompassing record – the blockchain’s immutable, single source of truth, if you will. It provides a high-level summary of all financial transactions, a consolidated view of the entire financial picture. This top-level ledger is fed by subsidiary ledgers, which are detailed records focusing on specific accounts or areas – like accounts receivable, accounts payable, or even specific crypto asset holdings. These subsidiary ledgers offer granular detail, allowing for deeper analysis and reconciliation. The general ledger’s summary data is derived from the aggregated information painstakingly recorded in these lower-level subsidiary ledgers. This structured approach ensures accuracy and provides both a comprehensive overview and the capability for in-depth scrutiny, mirroring the benefits of blockchain’s transparent and verifiable nature in a traditional accounting context.

This separation of duties, mirroring the decentralized nature of many crypto systems, improves efficiency and enhances auditability. Each subsidiary ledger can be managed by a different team, promoting accountability and reducing the risk of errors. Furthermore, this hierarchical structure allows for faster processing of individual transactions while maintaining the integrity and reliability of the overall financial picture represented in the general ledger. The analogy to a blockchain’s approach to data storage and verification is evident: a decentralized, verifiable system with granular details contributing to a consolidated, immutable truth.

What is general ledger distribution?

General ledger distribution? Think of it as the blockchain of your accounting. It’s the immutable record of how your revenue – your crypto gains, your NFT royalties, whatever – is flowing through your books. It’s not just a simple transaction; it’s a highly detailed breakdown.

Key insights revealed:

Account: Where the money landed – think specific wallets, different income streams.
Description: The narrative behind the transaction. Essential for tax season and auditing, especially crucial for complex DeFi yields or staking rewards.
Debit/Credit: The classic double-entry bookkeeping. Tracking increases and decreases in your assets and liabilities. Understand this, and you’ll understand your financial health far better than most.
Post Date: When the transaction hit the ledger. Time stamps are everything in the crypto world – timing affects tax implications profoundly.
Status: Is the transaction complete? Pending? Reconciled? Knowing the status prevents surprises and ensures everything matches up.

Why this matters to crypto investors:

Tax Optimization: Properly tracking distributions is paramount for minimizing your tax burden. Knowing the exact dates and amounts helps with accurate reporting.
Portfolio Management: Analyzing distributions provides a comprehensive view of your income and expenses across different crypto assets and platforms. This is vital for strategic decision-making.
Auditing and Security: A detailed general ledger provides an auditable trail, crucial for proving your transactions and protecting yourself from potential fraud.

Pro Tip: Don’t underestimate the power of granular accounting. The more detailed your general ledger distribution, the better equipped you are to manage your crypto wealth effectively.

What is the difference between distributed system and blockchain?

Fault tolerance is a key similarity: both distributed systems and blockchains aim for continuous operation despite node failures. However, their approaches differ significantly impacting their resilience and cost. Blockchains achieve fault tolerance through redundant ledgers, ensuring data integrity even with widespread node compromise. This inherent redundancy comes at a significant cost: higher bandwidth consumption and slower transaction speeds compared to distributed systems.

Distributed systems, on the other hand, prioritize data availability through replication. While data integrity is important, it’s not guaranteed to the same extent as blockchain. This means distributed systems can be more efficient, offering faster speeds and lower bandwidth usage. The trade-off is a potentially higher risk of data inconsistency or loss in extreme failure scenarios, depending on the specific replication strategy employed (e.g., quorum-based systems vs. eventual consistency). The choice between the two depends heavily on the application’s risk tolerance and performance requirements: high-value transactions prioritize blockchain’s guaranteed integrity, while high-throughput applications might favor the speed of a distributed system with its more nuanced data consistency guarantees.

Data consistency is another crucial divergence. Blockchain’s immutable ledger guarantees strong consistency across all nodes, although this comes at the expense of speed. Distributed systems offer various consistency models, ranging from strong consistency (mirroring blockchain’s properties) to eventual consistency (where data is eventually consistent across all nodes but not immediately). Understanding these nuances is critical for risk assessment and profitability in any trading environment.

Cost: Blockchain’s enhanced security and data integrity come at a premium. The computational overhead of consensus mechanisms and data replication significantly increases operational costs compared to distributed systems. This directly impacts transaction fees and infrastructure requirements, something any serious trader needs to factor in.

What is Merkle tree in distributed system?

A Merkle tree, in the context of a distributed system like a blockchain, is a genius way to verify data integrity efficiently. Imagine it as a hierarchical structure where each leaf node is a cryptographic hash of a data block (like a transaction in Bitcoin). Each node above the leaves then hashes the hashes of its children. This creates a single root hash at the top, representing the entire dataset. Think of it as a cryptographic fingerprint for the whole thing.

Why is this awesome for crypto? It allows for incredibly efficient verification. Instead of downloading and checking every single transaction to confirm a specific one’s validity, you only need the relevant branch of the Merkle tree and the root hash. This significantly reduces bandwidth and computation, making it perfect for lightweight clients.

The beauty lies in its security. If even a single bit of data in any transaction changes, it’ll propagate upwards, altering the root hash. This immediately flags any tampering. This is crucial for trust in blockchain systems where data immutability is paramount. The 2n branching factor (usually 2) just ensures a balanced and easily manageable tree structure.

Merkle trees are the backbone of efficient blockchain technology. They enable fast and secure verification of large datasets, making cryptocurrencies and other distributed ledger technologies truly scalable and reliable. They’re a core component of how we ensure trust in decentralized systems.

Are blockchain and DLT the same thing?

Think of DLT as the broad, overarching category – the entire crypto market, if you will. Blockchain is just one *specific* asset class within that market, albeit a dominant one. It’s like saying all squares are rectangles, but not all rectangles are squares. Blockchain uses chained blocks of data verified cryptographically. But DLT encompasses various architectures offering different trade-offs. Consider DAGs (Directed Acyclic Graphs) like IOTA, known for their scalability and speed, ideal for microtransaction environments. Hashgraph, with its unique consensus mechanism, promises superior speed and efficiency. Then there’s Holochain, a peer-to-peer DLT focusing on data sovereignty and agent-centric design, potentially useful for decentralized applications (dApps) needing more control. Each offers different advantages – scalability, speed, security – each affecting their suitability for various use cases and hence their potential investment value. Understanding these underlying technological differences is crucial for informed trading decisions within the DLT space.

Diversification is key: Don’t put all your eggs in one blockchain basket. Explore the potential of other DLTs. The future of DLT might not solely rely on blockchain’s dominance. Look at the underlying tech, the team, the market cap, and the use case – this will guide your investment strategy better than simply focusing on the “blockchain” label.

What is the difference between DLT and centralized?

Imagine a shared Google Doc, but instead of just a few people, everyone in the world can see and edit it. That’s kind of what a Distributed Ledger Technology (DLT) is. Instead of one company (like a bank) controlling all the information, the information is spread across many computers (nodes).

In a centralized system, like a traditional bank, all the data about your money is stored in one place – the bank’s server. If that server crashes, or the bank gets hacked, your information is at risk. With DLT, the data is replicated across many computers. If one computer fails, the others still have the complete information, making it much more secure and resilient.

DLT also means that everyone can see the same information, making it transparent and auditable. This is unlike a centralized system where only the central authority has full visibility. This transparency, along with the security, is what makes DLT exciting for things like cryptocurrencies and supply chain management.

However, DLT can also be more complex to manage and can be slower than centralized systems due to the need for consensus among many nodes.

What are the different types of distributed ledgers?

Distributed ledgers come in a few key flavors. Permissioned ledgers, like those used in many enterprise blockchain solutions, restrict access and participation to pre-approved entities. Think of it as a private club—only members can see the transactions. This allows for greater control and often, faster transaction speeds, but sacrifices decentralization and transparency.

Then there are public ledgers, the epitome of decentralization. Bitcoin and Ethereum are prime examples. Anyone can join the network, participate in consensus, and view all transactions. This transparency is a powerful feature, fostering trust and auditability, but it comes at the cost of scalability and potential vulnerability to attacks. The security here relies on massive distributed computing power—a double-edged sword.

Finally, we have private ledgers, often confused with permissioned ones. While access might be limited, a private ledger isn’t truly decentralized. A single entity (or a very small group) retains ultimate control, akin to a centralized database with distributed copies. This approach prioritizes performance and control but lacks the core decentralization benefits of blockchain technology. The trust here is placed entirely in the central authority, a crucial distinction.

What is difference between single ledger and multiple ledger?

Single ledger systems are simpler, offering a centralized view of all financial transactions. This is ideal for smaller operations or those with straightforward accounting needs. However, scalability becomes a major concern as the business grows; transaction processing can slow down significantly, and data integrity risks increase with larger datasets. Furthermore, single ledgers are vulnerable to single points of failure; a system crash means all records are inaccessible.

Multiple ledger systems, on the other hand, distribute the workload across multiple databases, boosting efficiency and scalability. This distributed architecture enhances resilience against failures; the loss of one ledger doesn’t compromise the entire system. Multiple ledgers also facilitate greater regulatory compliance and transparency, especially important in industries with strict reporting requirements. This distributed structure supports parallel processing, considerably accelerating transaction speeds and reducing latency, a crucial factor for high-frequency trading or other time-sensitive operations. However, implementation complexity and the need for robust synchronization mechanisms represent significant overhead compared to single ledgers.

The choice between single and multiple ledgers depends critically on the scale and complexity of the trading operation and its regulatory environment. While a single ledger is sufficient for smaller ventures, multiple ledger systems are essential for large-scale, high-velocity operations demanding superior scalability, resilience, and performance.

What is the difference between Merkle root and block hash?

The core difference between a Merkle root and a block hash lies in their scope and function within a blockchain. A block hash is a cryptographic fingerprint of an entire block, acting as its unique identifier. It’s a single, concise representation of all the data within that block—transactions, timestamps, the previous block’s hash (linking it to the chain), and importantly, the Merkle root.

The Merkle root, however, is a more intricate component. Imagine a binary tree where each leaf node represents a transaction’s hash. These hashes are paired and hashed together repeatedly until a single hash remains at the root—the Merkle root. This effectively summarizes all the transactions in a concise, verifiable manner. Think of it as a highly efficient way to verify the integrity of a large set of data. If even one transaction changes, the entire Merkle tree recalculates, resulting in a different Merkle root, and consequently, a different block hash.

This hierarchical structure offers significant advantages: it allows for efficient verification of individual transactions without needing to download the entire block. You can verify a specific transaction’s inclusion in the block by simply checking its path up the Merkle tree to the root. This is particularly useful for lightweight clients that don’t need to store the entire blockchain.

In essence, the Merkle root acts as a highly efficient summary of all transactions within a block, which is then incorporated into the block’s overall hash. The block hash, therefore, incorporates the Merkle root, along with other block data, to create its unique and tamper-evident identifier.

Is it Merkle or Merkle tree?

In cryptography, a Merkle tree (also known as a hash tree) is a fundamental data structure offering efficient and verifiable data integrity checks. It’s not simply “Merkle” – the “tree” is crucial to its functionality.

How it works: Each leaf node holds the cryptographic hash of a data block. Moving up the tree, each parent node’s hash is calculated from the hashes of its children. This creates a hierarchical structure where the root hash acts as a concise fingerprint of the entire dataset.

Key benefits:

Data Integrity Verification: By comparing the root hash with a previously stored value, you can quickly detect any alterations to the underlying data. Only a small portion of the data needs to be re-hashed to verify specific parts.
Efficient Data Aggregation: Merkle trees allow for efficient aggregation of data integrity proofs. Instead of verifying the entire dataset, you only need to verify the path from the leaf node to the root.
Scalability: As the dataset grows, the Merkle tree efficiently handles the increased data volume without significant performance degradation.

Applications:

Blockchain technology: Merkle trees are central to blockchain’s efficiency and security, allowing for verification of transaction blocks without downloading the entire blockchain.
Version control systems (like Git): They’re used to efficiently track changes and verify data integrity across different versions of files.
Secure file sharing and storage: Ensuring data hasn’t been tampered with during transmission or storage.
Digital signatures: Improving the efficiency and security of digital signatures by verifying parts of a large document.

In essence: A Merkle tree provides a computationally efficient way to verify the integrity of large datasets, making it a cornerstone of secure and scalable systems. The root hash acts as a single point of verification for the entire tree, enabling efficient and trustworthy data management.

What is the difference between distributed database and blockchain?

The core difference lies in immutability and consensus mechanisms. A distributed database, while storing data across multiple nodes, allows for data modification. Think of it like a sophisticated spreadsheet replicated across many computers; updates are possible, and data integrity relies on robust version control and synchronization protocols. This offers flexibility but requires trust in the system’s administrators.

A blockchain, however, is an append-only ledger. Once data is written (a block is added to the chain), it cannot be altered. This immutability is enforced through cryptographic hashing and a consensus mechanism (e.g., Proof-of-Work, Proof-of-Stake) ensuring all nodes agree on the chain’s validity. This eliminates the need for a central authority but sacrifices the flexibility to modify past records. This makes it ideal for applications requiring high trust and transparency, but less suitable for scenarios needing frequent data updates.

Distributed Databases: Ideal for applications needing high scalability and availability, offering efficient data management and allowing for data modification. Examples include cloud-based databases used in large-scale applications.
Blockchains: Best suited for applications requiring high transparency, immutability, and security, such as cryptocurrencies, supply chain management, and digital identity verification. Data modification is impossible post-transaction.

Practical implications for trading: Distributed databases underpin many high-frequency trading platforms enabling rapid data processing and order execution. Blockchains, while still nascent in mainstream finance, are exploring applications in clearing and settlement, potentially reducing counterparty risk and streamlining transactions through smart contracts. The immutable nature of a blockchain offers transparency that could benefit auditing and regulatory compliance, but the limitations on data modification pose challenges for certain trading activities requiring flexibility.

Scalability: Distributed databases generally offer superior scalability compared to current blockchain technologies.
Transaction Speed: Distributed databases offer significantly faster transaction speeds than many blockchains.
Cost: Maintaining a blockchain often incurs higher costs due to its energy-intensive consensus mechanisms compared to distributed databases.

What is the difference between distributed system and network system?

Think of computer networks as the plumbing – they facilitate communication and resource sharing. A network simply connects devices; it doesn’t inherently coordinate their actions towards a common goal. Scalability is achieved by adding more pipes (bandwidth), but this doesn’t inherently improve computational power.

Distributed systems, however, are like sophisticated trading algorithms. They’re designed to achieve a specific, often complex, objective by strategically distributing workloads across multiple nodes. This is not merely about sharing resources; it’s about coordinated computation. The power lies in the orchestration and parallelization of tasks, leading to significant performance gains beyond what you’d achieve by simply adding more single-node capacity.

Here’s a breakdown:

Computer Networks: Focus on communication; individual nodes operate independently; scalability primarily via increased bandwidth.
Distributed Systems: Focus on coordinated computation to achieve a shared goal; nodes collaborate closely; scalability achieved through distributed processing and fault tolerance.

Consider this analogy: A network is like a collection of individual traders, each operating independently. A distributed system is a sophisticated hedge fund, where algorithms coordinate numerous traders toward a unified investment strategy. The latter is far more complex, but offers potential for significantly greater returns (performance) and resilience (fault tolerance).

Key differences in a trading context:

Fault Tolerance: In a distributed system (like a robust trading platform), the failure of one node doesn’t necessarily bring down the entire system. In a simple network, a single point of failure can be catastrophic.
Data Consistency: Maintaining data consistency across numerous nodes in a distributed system is a significant challenge, requiring sophisticated protocols (think of real-time market data updates). Networks don’t face this level of complexity.
Latency: Distributed systems need to manage latency carefully – the delay between nodes affects performance and, in high-frequency trading, can mean the difference between profit and loss.

What is the difference between ledger database and blockchain?

Imagine a shared spreadsheet, that’s a distributed ledger. Many people can view and update it simultaneously. A blockchain is a *special type* of distributed ledger.

The key difference is how the updates are handled. In a regular distributed ledger, a central authority (like a bank) might control updates and verify their accuracy. Blockchains, however, use a clever system:

Decentralization: No single entity controls it. Many computers (nodes) across a network maintain a copy of the ledger.
Transparency (usually): Everyone can see the transactions (though identities might be hidden).
Immutability: Once a transaction is recorded in a “block” and added to the “chain,” it’s extremely difficult to alter or delete it. This is due to cryptographic hashing and consensus mechanisms.
Consensus mechanisms: These are rules that determine which transactions are valid and added to the chain. Examples include Proof-of-Work (used by Bitcoin) and Proof-of-Stake (used by Ethereum).

Think of it like this:

Transactions are gathered into “blocks”.
Each block is linked to the previous block using cryptography, forming a chain.
The network verifies the transactions in each block before adding it to the chain.

Not all distributed ledgers are blockchains. Some might use different consensus mechanisms or lack the same level of security and decentralization.