immudb data persistence (storage on disk)

The immudb storage layout consists of the following append-only logs per database:

  • AHT: Append-only Hash Tree. Each database has one main Merkle Tree where its inputs are built from transaction hashes. This tree is persisted in the storage layer. It is also appendable – each new transaction adds one extra leaf node with transaction hash (Alh) and rebuilds the path to the root. The AHT (Append-only Hash Tree) is a versioned Merkle tree where records are stored as digests left-to-right at the lowest level, following an append-only model. Like a hash chain, this AHT is persistent, with the difference that it supports efficient inclusion and consistency proofs. We can see that the AHT grows always from left to right. This growth property allows us to make efficient claims about the past because we can reconstruct old versions of the tree by pruning specific branches from right to left.
  • Transaction Log: An append-only log for storing the transaction headers for a transaction. This helps in reading the header information of a transaction easily, as the header size is fixed.
  • Commit Log: An append-only log for storing the information about the commits to a database. This log stores the transaction in an ordered way and is used for database recovery as transactions written in this log can be considered fully committed.
  • Value Log: An append-only log for storing the actual values of key-value pairs within a transaction. The underlying data structure is again an append-only log. This log is kept separate for faster reads, and because many other data structures internally refer to the values, storing it in a separate log provides ease of access. The B-Tree index and transaction headers do not store the value itself but refer to the offset of the value in the value-log appendable.
  • Index Log: An append-only log for storing the index for transactions in a database. Internally, immudb uses a B-Tree to index database records, and provide SQL support, and the index log is the B-Tree storage on disk.

Lifecycle of a transaction in immudb

When a transaction is sent to the immudb server, the following events take place:

  • Key-Values are encoded in a transaction
  • The values are recorded in the value-log appendable, and the offset of those values are stored in the transaction header (transaction log).
  • The accumulated linear hash (ALH) is built by chaining the hash of the current transaction + previous transactions ALH + the inner hash of the transaction. This value is then appended to the AHT where the merkle tree is stored and proofs are requested from.
  • There could be many concurrent transactions happening on the server, and the commit log stores information of transaction ordering. The Transaction header offset (from the transaction log) and size of the transaction are the only information stored in the commit log.
  • Lastly the keys and value offset information is stored in the B-Tree index, and the indexing happens asynchronously and can be recreated on a restart of the database.


You can check out the codebase here, also feel free to raise any doubts you have by creating an issue or joining our Discord:

Use Case - Tamper-resistant Clinical Trials


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.).


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


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.


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


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, …)


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


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.


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


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.


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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