DBMS > Couchbase vs. TimescaleDB

System Properties Comparison Couchbase vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Vector DBMS

Time Series DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS
Wide column store

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	13.82
Rank	#38	Overall
	#5	Document stores
	#3	Vector DBMS

Score	3.59
Rank	#72	Overall
	#5	Time Series DBMS

Website

www.couchbase.com

www.timescale.com

Technical documentation

docs.couchbase.com

docs.timescale.com

Developer

Couchbase, Inc.

Timescale

Initial release

2011

2017

Current release

Server: 7.6, March 2024; Mobile: 3.3, August 2024; Couchbase Capella (DBaaS), September 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

Server operating systems

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

full PostgreSQL SQL syntax

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month
2 June 2014, Matthias Gelbmann

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Recent citations in the news

Here's Why We're Not At All Concerned With Couchbase's (NASDAQ:BASE) Cash Burn Situation
7 May 2025, Yahoo Finance

Activist Investor Irenic Capital Builds Stake in Software Maker Couchbase
30 April 2025, Bloomberg.com

Subdued Growth No Barrier To Couchbase, Inc. (NASDAQ:BASE) With Shares Advancing 25%
4 May 2025, simplywall.st

Couchbase Unveils Edge Server to Help Organizations Solve Real-World Edge Application Challenges
4 March 2025, PR Newswire

Couchbase’s Regine Nelson brings authentic leadership to employee engagement
26 February 2025, Ragan Communications

provided by Google News

Timescale Bolsters AI-Ready PostgreSQL with pgai Vectorizer
20 November 2024, infoq.com

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft Azure

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

New TDengine Benchmark Results Show Up to 37.0x Higher Query Performance Than InfluxDB and TimescaleDB
28 February 2023, GlobeNewswire

provided by Google News

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