DBMS > CouchDB vs. GigaSpaces vs. Microsoft Azure AI Search vs. RocksDB vs. TypeDB

System Properties Comparison CouchDB vs. GigaSpaces vs. Microsoft Azure AI Search vs. RocksDB vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Search-as-a-service for web and mobile app development

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Search engine

Key-value store

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Spatial DBMS

using the Geocouch extension

Graph DBMS
Search engine

Vector DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

couchdb.apache.org

www.gigaspaces.com

azure.microsoft.com/en-us/services/search

rocksdb.org

typedb.com

Technical documentation

docs.couchdb.org/en/stable

docs.gigaspaces.com/latest/landing.html

learn.microsoft.com/en-us/azure/search

github.com/facebook/rocksdb/wiki

typedb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Gigaspaces Technologies

Microsoft

Facebook, Inc.

Vaticle

Initial release

2005

2000

2015

2013

2016

Current release

3.3.3, December 2023

15.5, September 2020

9.2.1, May 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

BSD

Open Source

GPL Version 3, commercial licenses available

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

Erlang

Java, C++, .Net

C++

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Solaris
Windows

hosted

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

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.

XML can be used for describing objects metadata

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-99 for query and DML statements

APIs and other access methods

RESTful HTTP/JSON API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

RESTful HTTP API

C++ API
Java API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.Net
C++
Java
Python
Scala

C#
Java
JavaScript
Python

C
C++
Go
Java
Perl
Python
Ruby

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Triggers

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

Implicit feature of the cloud service

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

substituted by the relationship feature

Transaction concepts

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

atomic operations within a single document possible

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

User concepts

Access control

Access rights for users can be defined per database

Role-based access control

yes

using Azure authentication

yes

at REST API level; other APIs in progress

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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Licensing and pricing models

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