Data is the foundation of every organization, so ensuring it’s reliable and consistent is essential in driving informed decisions and ensuring a sustainable growth. This is where data isolation comes into play.
Data isolation is all about separating and protecting individual transactions within a database. Keeping these transactions from interfering with one another promotes security, consistency, and integrity, which ultimately translate into high data quality.
What are the proven best practices for achieving data isolation? Keep reading for the essentials on data isolation.
What is Data Isolation?
Data isolation is fundamentally about separating and securing individual database transactions. Its primary goal is to ensure the reliability and integrity of your data.
When transactions are correctly isolated, they cannot interfere with one another, even if numerous users are attempting to access the same information at once. Isolating transactions ensures that changes made by one transaction are not visible to other transactions until committed, preventing potential conflicts.
That is where the ACID (Atomicity, Consistency, Isolation, and Durability) qualities are essential. The ‘I’ in ACID stands for Isolation – this principle that protects your data while ensuring consistent and trustworthy processes, whether you work locally or in the cloud.
Data Isolation and Air Gapping
When understood more in terms of data security, a modern data isolation strategy uses ‘virtual air gap‘ technology to safeguard backups with temporary network connections and very strict access controls, isolating data in the cloud when needed. This strategy creates a tamper-resistant environment while providing additional protection against ransomware and insider threats.
Why is Data Isolation Important?
Database isolation levels are significant because they govern the degree of consistency and correctness in a multi-user database. In a multi-user database system, transactions may overlap and access the same data concurrently, resulting in conflicts and inconsistencies if not properly managed.
Isolation levels allow you to limit the level of interaction and visibility between transactions, ensuring that concurrent transactions do not conflict while producing correct and consistent results.
Databases are expected to manage concurrent transactions from multiple users. Unfortunately, not everything can run in parallel. Managing a greater isolation level has become increasingly intriguing because it improves data consistency while addressing potential drawbacks such as increased memory utilization, congestion, and reduced concurrency that come with stricter isolation levels.
Choosing the right isolation level for a database system is key – and numerous criteria are relevant, including the required level of consistency, performance requirements, and the specific types of transactions and access patterns.
Each isolation level not only provides a lower or higher level of consistency and correctness, but it also impacts the potential performance of locking. Keep in mind that isolation levels vary by vendor implementation and may be less or greater than theoretically indicated.
How Does Data Isolation Work?
Organizations can establish different levels of data isolation. For security purposes, tactics range from entirely disconnecting systems (physically and virtually) to using temporary network connections with layered access controls. The idea is to strike a balance between isolation and business continuation. Each isolation approach enhanced by air gap technology must contribute to the organization’s RTO/RPO objectives.
Since total physical and electronic isolation (as defined in textbooks) does not meet the majority of today’s company needs, innovative isolation solutions based on robust access restrictions and transient network connections have arisen.
When we consider isolation from the perspective of ACID transactions, the picture looks different:
Isolated transactions are deemed “serializable,” which means that each transaction occurs in a distinct order, with no transactions occurring simultaneously. Any reads or writes conducted on the database won’t be affected by other reads and writes from distinct transactions taking place on the same database.
A global order is created, with each transaction queued up in order to ensure that all transactions are completed before the next one begins. Still, multiple transactions are allowed as long as they do not have the potential to affect other transactions that are taking place simultaneously.
This can impact transaction speed because it forces several activities to wait before initiating. This cost, however, is worthwhile given the increased data security provided by isolation.
4 Levels of Data Isolation
Databases can use four different levels of data isolation, each of which impacts transaction management and data integrity. Let us break them down:
| Challenge | Description |
|---|---|
| Read Uncommitted | This is the lowest level where transactions can access data that has not yet been committed. While this may be acceptable in some cases, it also allows for “dirty reads,” which means working with partial or erroneous information. |
| Read Committed | This level is more widely utilized. Read Committed assures that transactions can only access data that has been committed, avoiding the dangers of the previous level. This provides a fair blend of data security and performance. |
| Repeatable Read | This level avoids “non-repeatable” or “phantom” reads, in which the same query is conducted twice during a transaction and yields different results. However, increased isolation requires more resources. |
| Serializable | The most advanced degree of data isolation, Serializable ensures complete separation between transactions by locking resources. Although this eliminates the chance of interference, the serialization of transactions can have a considerable influence on database performance. |
Key Techniques in Data Isolation
Implementing Isolation via ACID Transactions
Isolation can be implemented as part of a broader ACID transaction implementation.
ACID transactions are a set of attributes used to assure the reliability and consistency of database transactions.
Essentially, ACID transactions ensure that database operations are carried out correctly and that if a problem occurs, the database may recover to a prior state without losing any data or affecting the data’s consistency. In other words, ACID transactions ensure that database operations are completed reliably and data is saved precisely and consistently.
ACID transactions ensure data integrity by following a process like this:
- Begin Transaction – A BEGIN TRANSACTION statement declaration starts a transaction and creates a savepoint from which the transaction can be reversed if necessary.
- Execute operations – Each operation in the transaction is performed one at a time. The database validates each action to ensure that it follows the constraints and structure.
- Commit or Rollback – After all activities have been successfully completed, the transaction is committed using the COMMIT statement. If any operation fails, the transaction is rolled back to the initial savepoint.
The procedures outlined here are a standard technique for databases to handle ACID transactions, but there may be changes or discrepancies in implementation depending on the database system utilized.
Strike a Balance Between Optimistic and Pessimistic Transaction Model
Isolation can be achieved by using a sliding scale of permissiveness that ranges from optimistic to pessimistic transactions:
- An optimistic transaction model anticipates that subsequent transactions will be completed without reading or writing to the same location twice. If a transaction hits the same spot again, the optimistic schema will abort and retry.
- A pessimistic transaction schema restricts resources and assumes that one transaction will affect another. This leads to fewer aborts and retries, but it also implies that transactions must wait in line for their turn more frequently than with the optimistic transaction strategy.
Finding a balance between these two principles is frequently where you’ll get the finest overall results.
Data Isolation Use Cases
ACID transactions are suited for a variety of applications, among them:
Financial Services
Banks employ ACID transactions to ensure accurate and secure financial transactions. For example, when a customer withdraws money from an ATM, an ACID transaction is initiated to update their account balance and record the activity. The transaction is atomic, which means it succeeds or fails while the account balance remains constant.
Healthcare Systems
Electronic health records (EHRs) contain personal information about patients that must be correct and consistent. ACID transactions are used in healthcare systems to ensure that patient records are correctly updated and confidential medical data is preserved.
For example, an ACID transaction occurs when a doctor updates a patient’s medicine in the EHR to ensure that the data is updated atomically, consistently, and permanently.
e-Commerce Applications
ACID transactions are used in e-commerce applications to ensure that consumer orders are appropriately processed and inventory levels are accurately updated.
For example, when a customer purchases an item, an ACID transaction is performed to update inventory data and ensure that the transaction is atomic, consistent, isolated, and durable.
Benefits of Data Isolation
When talking about the benefits of data isolation, it’s impossible not to consider the border advantages of ACID transactions:
Data integrity
Using ACID-compliant systems ensures that your data is accurate, valid, and meets the limitations you set for the system.
Streamlined Operational Logic
Complex updating activities won’t require prior examination or planning based on reciprocal interaction mechanisms. Simply commit them, and the DBMS system will handle isolation and consistency.
Reliable Storage
In-memory storage frequently fails. This is why having access to long-lasting storage alleviates operational concerns.
Challenges of Data Isolation
Implementing ACID transactions presents several challenges, especially in distributed systems.
Distributed systems comprise many computers that work together to provide a single service. ACID transactions can be challenging to implement in distributed systems because they involve numerous physically separated nodes and communicate via a network.
Teams need to consider the following challenges:
| Challenge | Description |
|---|---|
| Network Latency | In distributed systems, network latency can affect the performance of ACID transactions. Network connection delays can lead to longer transaction times and more overhead. |
| Consistency | Maintaining consistency across all distributed system nodes can be difficult. A distributed system’s nodes may store copies of the same data, resulting in inconsistencies. |
| Availability | Keeping a distributed system operational can be challenging. Nodes may fail, making it difficult to keep the system responsive. |
| Scalability | As the number of nodes in a distributed system grows, it becomes more difficult to ensure consistency and availability. |
Impact of Data Isolation on Performance
Concurrency control is an important part of database management systems (DBMS). It ensures that several transactions can access and modify data concurrently without affecting dependability. However, the isolation degree you select considerably impacts your system’s performance.
It’s difficult to balance protecting data integrity through isolation and increasing system performance.
Higher isolation levels, such as Serializable, offer the most robust protection by tightly isolating transactions. However, this comes at a cost of lower transaction throughput and higher latency. Lower isolation levels, such as Read Uncommitted, improve performance but make you more susceptible to interference.
Best Practices for Data Isolation
These best practices are critical for maintaining ACID features and assuring transactional databases’ dependability, integrity, and security. Organizations can preserve data consistency and dependability by employing strong transaction management, concurrency control, and backup and recovery techniques, which protect important business operations and ensure continuous access to vital information.
Implement Reliable Transaction Management Technologies
This is how you can ensure atomicity and consistency in database operations. To maintain data integrity, properly manage transaction boundaries, rollback methods, and commit protocols.
Use the Right Concurrency Control Solutions
Use appropriate concurrency control technologies to maintain isolation and prevent data interference among concurrent transactions. Locking, multi-version concurrency control (MVCC), and optimistic concurrency control are all strategies for managing concurrent access to shared resources.
Use Solid Backup and Recovery Strategies
Create thorough backup and recovery mechanisms to assure the integrity and recoverability of committed transactions. Backup database files, transaction logs, and system snapshots regularly to avoid data loss and allow for quick recovery in the case of a system failure or disaster.
Methods of Implementing Data Isolation
Implementing ACID characteristics in databases requires careful database system design and implementation. The following are some of the most important aspects to consider when ensuring ACID compliance.
1. Transaction Management
As a fundamental notion, the database system must handle transactions and provide procedures for initiating, committing, and rolling back transactions. The system must also ensure that transactions are atomic, which means that all trade operations succeed or fail simultaneously.
2. Consistency Checks
The database system must impose consistency requirements such as data type checks, referential integrity, and business rules. To ensure database consistency, the system must validate data before committing changes.
3. Isolation Levels
The database system must have multiple isolation levels to handle concurrent transactions. The system must ensure that transactions are segregated so that one doesn’t impact the outcome of another.
4. Transaction Logs
The database system must preserve transaction logs to ensure its longevity. The registers must record all transactions’ modifications before they are applied to the database. In the event of a failure, the system must be able to use these logs to restore the database to a consistent state.
5. Backup and Recovery
If something goes wrong, the database system must have methods to back up and recover the data. This could include generating regular database backups, retaining redundant copies of the data, or implementing high-availability techniques like replication and clustering.
6. Use a DSBM Solution That Supports ACID
To implement ACID qualities in a database system, utilize a DBMS that supports them. SQL platforms, Oracle, Microsoft SQL Server, PostgreSQL, and MySQL are popular database management systems supporting ACID features.
Additionally, you can design your database structure and application code to ensure that transactions follow the ACID properties. For example, stored procedures and triggers can enforce constraints and ensure that trades are done atomically.
7. Don’t Forget About Testing
Finally, extensively test your application to ensure it operates correctly in various failure scenarios.
Data Isolation with lakeFS
In the world of databases, a transaction is a unit of work that includes one or more activities, such as inserting, updating, and removing records.
The important aspect of a transaction is its atomicity, which means that all operations within the transaction are viewed as a single, indivisible entity. Ideally, transactions adhere to the ACID properties, which ensure reliability and data integrity.
Data version control solutions like lakeFS help to model such transactional notions.
While lakeFS doesn’t directly implement typical database transactions, it does provide a versioning system and branching techniques to handle changes in the data lake, allowing for the modeling of transactional notions.
In the context of lakeFS, a “transaction” is a set of changes performed to our data lake, such as adding, updating, or removing items. The versioning technique enables you to track these changes over time and, if necessary, revert to a previous state, resulting in consistency and traceability.
In reality, you may replicate transactions in lakeFS by branching out from the source branch, completing all of the transaction’s needed operations, and then merging the side branch back into the source branch.
lakeFS’s high-level SDK transaction mechanism closely resembles traditional database systems’ Read committed isolation level. In this mode, a transaction reads only committed data, preventing dirty reads; this is accomplished by using lakeFS’s version control system (branching and merging).
Read this article to learn more about how lakeFS supports ACID transactions: lakeFS Transactions: Maintain Data Integrity Using ACID Principles
Conclusion
Data isolation is more than just a technical “must-have”; it is a strategic need that, luckily, is often a by-product of data version control best practices. ACID transactions contribute to data integrity and reliability while assuring that essential data subject to governmental or industry regulation meets the necessary criteria. Furthermore, ACID compliance is frequently required to replicate data and ensure high availability in distributed database environments.
