DBMS > Couchbase vs. H2GIS vs. Hive vs. Ignite vs. OrientDB

System Properties Comparison Couchbase vs. H2GIS vs. Hive vs. Ignite vs. OrientDB

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

Spatial extension of H2

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store

Spatial DBMS

Relational DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store

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

Relational DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

Technical documentation

docs.couchbase.com

www.h2gis.org/docs/home

cwiki.apache.org/confluence/display/Hive/Home

apacheignite.readme.io/docs

www.orientdb.com/docs/last/index.html

Developer

Couchbase, Inc.

CNRS

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

OrientDB LTD; CallidusCloud; SAP

Initial release

2011

2013

2012

2015

2010

Current release

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

3.1.3, April 2022

Apache Ignite 2.6

3.2.29, March 2024

License

Commercial or Open Source

Open Source

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

Open Source

LGPL 3.0

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Go and Erlang

Java

C++, Java, .Net

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language, no joins

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

JDBC
ODBC
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java

C++
Java
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

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

yes

based on H2

yes

user defined functions and integration of map-reduce

yes (compute grid and cache interceptors can be used instead)

Java, Javascript

Triggers

yes

via the TAP protocol

yes

yes (cache interceptors and events)

Hooks

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

based on H2

selectable replication factor

yes (replicated cache)

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

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

yes

based on H2

Access rights for users, groups and roles

Security Hooks for custom implementations

Access rights for users and roles; record level security configurable

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