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Architecture

Tigris is built using cloud-native principles and provides a serverless experience where it is able to seamlessly scale with your applications.

It separates Query, Index and the Storage layers and allows these layers to be scaled independently based on the workload needs. By designing Tigris using a cloud native architecture, it provides users with incredible flexibility to run various types of workloads as well as the ability to achieve massive scale.

Cloud Native Architecture

At the heart of the document store is FoundationDB. FoundationDB is a distributed key-value store that enables nearly limitless scalability.

FoundationDB as the data persistence layer

FoundationDB is used by Apple, Snowflake, and countless others as a stand-alone, production-ready distributed key-value store with interactive transactions. It provides the same consistency guarantees as Spanner (strict serializability), and has an amazing correctness story through simulation testing. FoundationDB exposes a key-value API, similar to RocksDB, but it scales to support petabytes of data and millions of operations per second in a single deployment on a modest amount of commodity hardware.

FoundationDB Architecture

(reference: https://apple.github.io/foundationdb/architecture.html)

Tigris uses FoundationDB’s transactional key-value interface as its underlying storage engine.

Tigris leverages FoundationDB to handle durability, replication, sharding, transaction isolation, and load balancing. FoundationDB provides Tigris with extremely powerful workload management features. The database is constantly evaluating the load of the cluster to determine when it is “too busy”, and when that happens it will artificially slow down starting new transactions until the load is stable again. By forcing all the latency to the beginning of your transaction, FoundationDB ensures every operation after that experiences a consistent, low latency. Many other database systems lack any workload management features at all, which manifests as overloaded clusters requiring operators to shut down all the clients to get it back under control.

Read more about why we chose FoundationDB here.

Cloud native architecture

Tigris was designed to separate critical components into independently scalable pieces. Tigris separates Query, Index and the Storage layers and allows these layers to be scaled independently based on the workload needs.

By designing Tigris using a cloud native architecture, it provides users with incredible flexibility to run various types of workloads as well as the ability to achieve massive scale.

Query processing

Applications using Tigris make use of its universal APIs to handle all the complex data interactions. Tigris natively provides HTTP APIs and uses JSON for transmitting data. Besides that, the Tigris API can be accessed directly in your favorite languages. Currently, Typescript, Java and Go libraries are available.

The user queries interact with the Tigris query layer that performs the necessary validations (permissions, schema, quotas), generates a query plan and then executes the query.

Indexing

Under the hood, Tigris has implemented a fork of the popular open source search tool Typesense and uses it to intelligently index the documents. This means there is no need to worry about manually indexing documents or collections and no need for detailed query tuning optimization exercises. The indexing store can also be scaled independently of other components.

Tigris has search built in, and you don't need a separate platform to access robust search capabilities, it works out of the box. Both search and query functionality share the same indexes and are serviced by the same indexing store under the hood.

Tigris in a nutshell

Tigris provides a cohesive, flexible set of tools for application developers to take an idea from production without stepping into the sinkhole of data pipelines, broken sync jobs, and complicated concurrency bugs present in many modern application architectures. As your data grows, so does Tigris, with a cloud-native architecture designed for scaling.