DBMS > Couchbase vs. InfluxDB vs. Newts vs. PostGIS

System Properties Comparison Couchbase vs. InfluxDB vs. Newts vs. PostGIS

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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

DBMS for storing time series, events and metrics

Time Series DBMS based on Cassandra

Spatial extension of PostgreSQL

Primary database model

Document store

Time Series DBMS

Spatial 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

Spatial DBMS

with GEO package

Relational DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.couchbase.com

www.influxdata.com/products/influxdb-overview

opennms.github.io/newts

postgis.net

Technical documentation

docs.couchbase.com

docs.influxdata.com/influxdb

github.com/OpenNMS/newts/wiki

postgis.net/documentation

Developer

Couchbase, Inc.

OpenNMS Group

Initial release

2011

2013

2014

2005

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

2.7.6, April 2024

3.4.2, February 2024

License

Commercial or Open Source

Open Source

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

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Open Source

GPL v2.0

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

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X

through Homebrew

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language

yes

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
JSON over UDP

HTTP REST
Java API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Java

Server-side scripts

Stored procedures

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

user defined functions

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

in enterprise version only

Sharding

based on Cassandra

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

in enterprise version only

selectable replication factor

based on Cassandra

yes

based on PostgreSQL

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes

Depending on used storage engine

User concepts

Access control

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

simple rights management via user accounts

yes

based on PostgreSQL

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
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