Important: This documentation is about an older version. It's relevant only to the release noted, many of the features and functions have been updated or replaced. Please view the current version.
Legacy storage
Warning
The concepts described on this page are considered legacy and pre-date the single store storage introduced in Loki 2.0. The usage of legacy storage for new installations is highly discouraged and documentation is meant for informational purposes in case of upgrade to a single store.
The chunk store is the Loki long-term data store, designed to support interactive querying and sustained writing without the need for background maintenance tasks. It consists of:
- An index for the chunks. This index can be backed by:
- A key-value (KV) store for the chunk data itself, which can be:
Note
Unlike the other core components of Loki, the chunk store is not a separate service, job, or process, but rather a library embedded in the two services that need to access Loki data: the ingester and querier.
The chunk store relies on a unified interface to the “NoSQL” stores (DynamoDB, Bigtable, and Cassandra) that can be used to back the chunk store index. This interface assumes that the index is a collection of entries keyed by:
- A hash key. This is required for all reads and writes.
- A range key. This is required for writes and can be omitted for reads, which can be queried by prefix or range.
The interface works somewhat differently across the supported databases:
- DynamoDB supports range and hash keys natively. Index entries are thus modelled directly as DynamoDB entries, with the hash key as the distribution key and the range as the DynamoDB range key.
- For Bigtable and Cassandra, index entries are modelled as individual column values. The hash key becomes the row key and the range key becomes the column key.
A set of schemas are used to map the matchers and label sets used on reads and writes to the chunk store into appropriate operations on the index. Schemas have been added as Loki has evolved, mainly in an attempt to better load balance writes and improve query performance.