Frostdb

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FrostDB is an embeddable column database written in Go, optimized for analytical workloads with high write volumes. It features semi-structured schemas and uses Apache Parquet for storage and Apache Arrow for queries.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is frostdb?

FrostDB is an embeddable wide-column columnar database written in Go, designed for analytical workloads where the majority of interactions are writes, with occasional analytical queries. It leverages Apache Parquet for efficient storage and Apache Arrow for vectorized query execution. A key differentiator is its support for dynamic columns, allowing schemas to evolve at runtime, which is particularly useful for observability data like Prometheus time-series. The database maintains data immutability and uses an LSM-like index for storage, with snapshot isolation for reads. While still in its infancy and not production-ready, FrostDB offers a compelling solution for Go developers needing an embedded, high-performance columnar database for immutable, semi-structured datasets.

Best used for

Ideal for developers who need to embed a high-performance columnar database directly into their Go applications, handle semi-structured data with dynamic schemas, and perform analytical queries on immutable datasets. Especially valuable for observability use cases where data is primarily written and occasionally queried.

Common actions

embed database

store columnar data

perform analytical queries

manage dynamic schemas

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Capabilities

Key features

Embeddable Go database
Dynamic column schemas
Apache Parquet storage
Apache Arrow queries
Immutable data
Snapshot isolation

Target Audience

developer

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the primary use cases for FrostDB?

FrostDB is optimized for scenarios with high write volumes and occasional analytical queries, particularly in observability. It's designed for embedding within Go programs and handling immutable, semi-structured datasets where schemas might evolve dynamically, such as time-series data with varying labels.

Does FrostDB support modifying or deleting data?

No, FrostDB is built around the principle of immutable data. It only supports writes and reads. If your application requires the ability to modify or delete existing data, FrostDB is likely not suitable for your needs.

How does FrostDB handle dynamic columns?

FrostDB allows you to define a column as dynamic, meaning new columns can be created on the fly when new label-names are encountered in your data. This is particularly useful for data with evolving schemas, like Prometheus time-series, where label sets are not known upfront.

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