immudb v1.3.2, the immutable database handles a very large volume of small tx

Our new immudb release 1.3.2 just went out to the public. It is now available via github and docker hub. This release is about more performance and more logging.

While performance using batch operations was already very fast, we wanted to improve single transaction performance as well. Everyone likes a higher throughput, but the initial requests came from our FinTech community that asked an immutable database that can handle a very large volume of small transactions.

The other improvement concerns logging, especially machine-readable logging. As we see more automatic deployments on AWS, Elestio and other hosting platforms, that was an important task to finish.

Details of the performance improvements

Performance was the main focus of this immudb release. The way durability guarantees were implemented until now i.e. fsync was called synchronously as the final commit step, resulted in a lot of overhead for each transaction.

A significant improvement in write performance (up to x10 faster compared to previous immudb release v1.3.1) was achieved by grouping transactions in the last step of the commit process. The gains are greatest when there are fewer key-value entries per transaction and multiple writers are simultaneously working.

The cost of the sync operation pays for itself as the number of key-value pairs in each transaction increases, although some noticeable speed can still be achieved (up to x2 compared to previous immudb release v1.3.1).

Read performance was also significantly improved due to the introduction of reusable pools of objects, which reduced allocations needed during query resolution. The gains are quite significant in both single and multi-get operations.

JSON Logging

Logs can also be generated in json format for easier ingestion by logging platforms.
It’s quite simple to enable this useful feature, just run immudb with the logformat flag set to json e.g. ./immudb --logformat=json

There’s so much more!

You can read the complete release notes on github https://github.com/codenotary/immudb/releases/tag/v1.3.2 to see the complete changelog and read more about all the great features, fixes, and enhancements in this release. Make sure you check it out.

What are you building?

The feedback from the community has been tremendous and we love to hear what y’all are building. It’s what keeps us going day after day. Join us on Discord and Twitter to follow what we’re doing and let us know what you’re doing.

immudb

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Use Case - Tamper-resistant Clinical Trials

Goal:

Blockchain PoCs were unsuccessful due to complexity and lack of developers.

Still the goal of data immutability as well as client verification is a crucial. Furthermore, the system needs to be easy to use and operate (allowing backup, maintenance windows aso.).

Implementation:

immudb is running in different datacenters across the globe. All clinical trial information is stored in immudb either as transactions or the pdf documents as a whole.

Having that single source of truth with versioned, timestamped, and cryptographically verifiable records, enables a whole new way of transparency and trust.

Use Case - Finance

Goal:

Store the source data, the decision and the rule base for financial support from governments timestamped, verifiable.

A very important functionality is the ability to compare the historic decision (based on the past rulebase) with the rulebase at a different date. Fully cryptographic verifiable Time Travel queries are required to be able to achieve that comparison.

Implementation:

While the source data, rulebase and the documented decision are stored in verifiable Blobs in immudb, the transaction is stored using the relational layer of immudb.

That allows the use of immudb’s time travel capabilities to retrieve verified historic data and recalculate with the most recent rulebase.

Use Case - eCommerce and NFT marketplace

Goal:

No matter if it’s an eCommerce platform or NFT marketplace, the goals are similar:

  • High amount of transactions (potentially millions a second)
  • Ability to read and write multiple records within one transaction
  • prevent overwrite or updates on transactions
  • comply with regulations (PCI, GDPR, …)


Implementation:

immudb is typically scaled out using Hyperscaler (i. e. AWS, Google Cloud, Microsoft Azure) distributed across the Globe. Auditors are also distributed to track the verification proof over time. Additionally, the shop or marketplace applications store immudb cryptographic state information. That high level of integrity and tamper-evidence while maintaining a very high transaction speed is key for companies to chose immudb.

Use Case - IoT Sensor Data

Goal:

IoT sensor data received by devices collecting environment data needs to be stored locally in a cryptographically verifiable manner until the data is transferred to a central datacenter. The data integrity needs to be verifiable at any given point in time and while in transit.

Implementation:

immudb runs embedded on the IoT device itself and is consistently audited by external probes. The data transfer to audit is minimal and works even with minimum bandwidth and unreliable connections.

Whenever the IoT devices are connected to a high bandwidth, the data transfer happens to a data center (large immudb deployment) and the source and destination date integrity is fully verified.

Use Case - DevOps Evidence

Goal:

CI/CD and application build logs need to be stored auditable and tamper-evident.
A very high Performance is required as the system should not slow down any build process.
Scalability is key as billions of artifacts are expected within the next years.
Next to a possibility of integrity validation, data needs to be retrievable by pipeline job id or digital asset checksum.

Implementation:

As part of the CI/CD audit functionality, data is stored within immudb using the Key/Value functionality. Key is either the CI/CD job id (i. e. Jenkins or GitLab) or the checksum of the resulting build or container image.

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