DBMS > Apache Pinot vs. Couchbase vs. GeoSpock vs. KairosDB

System Properties Comparison Apache Pinot vs. Couchbase vs. GeoSpock vs. KairosDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Spatial and temporal data processing engine for extreme data scale

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

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

Time Series DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Website

pinot.apache.org

www.couchbase.com

geospock.com

github.com/kairosdb/kairosdb

Technical documentation

docs.pinot.apache.org

docs.couchbase.com

kairosdb.github.io

Developer

Apache Software Foundation and contributors

Couchbase, Inc.

GeoSpock

Initial release

2015

2011

2013

Current release

1.0.0, September 2023

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

2.0, September 2019

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

commercial

Open Source

Apache 2.0

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

Java

C, C++, Go and Erlang

Java, Javascript

Java

Server operating systems

All OS with a Java JDK11 or higher

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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

temporal, categorical

SQL

Support of SQL

SQL-like query language

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

ANSI SQL for query only (using Presto)

APIs and other access methods

JDBC

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

JDBC

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

Go
Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

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

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Automatic Sharding

Automatic sharding

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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.

Access rights for users can be defined per table

simple password-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.