DBMS > Couchbase vs. ReductStore vs. TempoIQ

System Properties Comparison Couchbase vs. ReductStore vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

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

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Trend Chart

Score	16.01
Rank	#35	Overall
	#5	Document stores
	#2	Vector DBMS

Score	0.00
Rank	#375	Overall
	#40	Time Series DBMS

Website

www.couchbase.com

github.com/reductstore
www.reduct.store

tempoiq.com (offline)

Technical documentation

docs.couchbase.com

www.reduct.store/docs

Developer

Couchbase, Inc.

ReductStore LLC

TempoIQ

Initial release

2011

2023

2012

Current release

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

1.9, March 2024

License

Commercial or Open Source

Open Source

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

Open Source

Business Source License 1.1

commercial

Cloud-based only

Only available as a cloud service

yes

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

C++, Rust

Server operating systems

Linux
OS X
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

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

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

HTTP API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C++
JavaScript (Node.js)
Python
Rust

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

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

Triggers

yes

via the TAP protocol

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

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

Foreign keys

Referential integrity

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.

simple authentication-based access control

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