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Datalayers

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by Datalayers · since 2024 · also known as DataLayers

Multi-model database for IoT and observability: time series, full-text, vector and key-value on Parquet.

time-seriessearch enginevectorkey-valuecolumnar / olapdatabase engineproprietaryemerging
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Overview

Datalayers is a commercial distributed database from China aimed at observability, IoT and AI retrieval. It combines time-series storage, BM25 full-text search, vector search (IVF and HNSW), a Redis-compatible key-value model and SQL stream processing behind one SQL interface, with storage and compute separated over object storage in Parquet format. Clients connect over the PostgreSQL wire protocol or Arrow Flight SQL, and it accepts InfluxDB line protocol and Prometheus remote write, so existing collectors plug in. It is designed to run on edge gateways as well as in cloud clusters. Releases are frequent, but documentation is mostly in Chinese and the product is licence-key based rather than open source.

IoT & telemetryObservabilityTime-series dataFull-text searchVector searchEdge & serverlessStream processing

Strengths & trade-offs

Strengths

  • +Time series, full-text, vector and key-value data in one SQL engine
  • +Parquet on object storage keeps data readable by big-data tools
  • +Built-in stream ingestion from Kafka, MQTT and HTTP with SQL pipelines
  • +Federated queries join MySQL and PostgreSQL tables
  • +Runs on resource-constrained edge gateways

Trade-offs

  • −Closed source with licence-key activation
  • −Very young product with few public references
  • −Documentation is mainly in Chinese
  • −Breadth of features means less depth than specialist engines

Great for

  • +Industrial IoT data platforms
  • +Unified metrics, logs and events storage
  • +Hybrid keyword and vector retrieval for AI apps
  • +Edge-to-cloud telemetry

Think twice for

  • −Teams requiring open source
  • −Transactional workloads
  • −Organisations needing English-first support

Capabilities

Native or official first-party support · 10 of 25 tracked

✓Joins
✓Secondary indexes
✓Full-text search
✓Vector search
✓TTL / expiry
✓Columnar storage
✓Durable persistence
✓Compression
✓Role-based access
✓Streaming ingest
–Transactions
–Geospatial
–JSON
–Change data capture
–Triggers
–Stored procedures
–Materialized views
–Pub/Sub
–In-memory
–Encryption at rest
–Time travel
–Branching
–Online schema changes
–Offline sync
–Runs in WebAssembly

Scale & consistency

Comfortable data size
Large · ≤ 1 PB
Horizontal scaling
Native
Multi-region
No
Transactions
None
Consistency
Eventual
Schema
Strict
Architecture
Single node, Distributed, Shared storage
Query languages
SQL, PromQL

Compute and storage scale independently over S3-compatible object storage.

Deployment

Self-hosted Vendor-managed cloud Serverless Embedded Edge Kubernetes operator

Ecosystem

compatible withPostgreSQL, InfluxDB, Prometheus, Redis
apis & protocolsPostgreSQL wire protocol, Arrow Flight SQL, InfluxDB line protocol, Prometheus remote write, Redis protocol, REST, JDBC

Alternatives to Datalayers

Compare all→
TDengineTime-Series17.4

Industrial-IoT time-series database with a table-per-device model and built-in streaming and caching.

datalayers vs tdengine →
GreptimeDBTime-Series15.1

Rust observability database that keeps metrics, logs and traces in one columnar engine on object storage.

datalayers vs greptimedb →
InfluxDBTime-Series51.0

Purpose-built time-series database, rebuilt in Rust on Arrow, DataFusion and Parquet for version 3.

datalayers vs influxdb →
Apache IoTDBTime-Series22.8

Apache time-series database for industrial IoT with tree and table models and edge-to-cloud sync.

datalayers vs apache-iotdb →
MachbaseTime-Series3.1

Korean time-series database for sensor data, bundled with MQTT, HTTP and dashboards in one binary.

datalayers vs machbase →
CnosDBTime-Series6.7

Rust cloud-native time-series database with SQL on DataFusion and InfluxDB-style ingestion.

datalayers vs cnosdb →

Datalayers FAQ

What is Datalayers?

Datalayers is a time-series database by Datalayers, first released in 2024. Datalayers is a commercial distributed database from China aimed at observability, IoT and AI retrieval. It combines time-series storage, BM25 full-text search, vector search (IVF and HNSW), a Redis-compatible key-value model and SQL stream processing behind one SQL interface, with storage and compute separated over object storage in Parquet format. Clients connect over the PostgreSQL wire protocol or Arrow Flight SQL, and it accepts InfluxDB line protocol and Prometheus remote write, so existing collectors plug in. It is designed to run on edge gateways as well as in cloud clusters. Releases are frequent, but documentation is mostly in Chinese and the product is licence-key based rather than open source.

Is Datalayers open source?

No. Datalayers is proprietary, closed-source software. License: Commercial (licence key; free trial).

Does Datalayers support ACID transactions?

No. Datalayers does not provide ACID transactions; its consistency model is eventual.

Does Datalayers scale horizontally?

Datalayers scales horizontally out of the box, with built-in sharding or partitioning. It is comfortable at large scale (≤ 1 PB).

How can I run Datalayers?

You can self-host it and run it at the edge.

What is Datalayers best for?

Datalayers is a strong fit for industrial IoT data platforms; unified metrics, logs and events storage; and hybrid keyword and vector retrieval for AI apps. Think twice for teams requiring open source.

What are the best alternatives to Datalayers?

Common alternatives to Datalayers include TDengine, GreptimeDB, InfluxDB, Apache IoTDB and Machbase. The right choice depends on your workload, scale and hosting; WhichDB's smart match ranks them against your requirements.

How popular is Datalayers?

Datalayers ranks #520 of 844 databases on the WhichDB Score (1.7/100), and #33 among time-series databases. The score combines public adoption signals such as package downloads, GitHub activity, job posts and developer discussion.