DBMS > GridGain vs. JaguarDB vs. Microsoft Azure SQL Database vs. OpenSearch vs. Quasardb

System Properties Comparison GridGain vs. JaguarDB vs. Microsoft Azure SQL Database vs. OpenSearch vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Performant, highly scalable DBMS for AI and IoT applications

Database as a Service offering with high compatibility to Microsoft SQL Server

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Distributed, high-performance timeseries database

Primary database model

Key-value store
Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Vector DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

www.gridgain.com

www.jaguardb.com

azure.microsoft.com/en-us/products/azure-sql/database

github.com/opensearch-project
opensearch.org

quasar.ai

Technical documentation

www.gridgain.com/docs/index.html

www.jaguardb.com/support.html

docs.microsoft.com/en-us/azure/azure-sql

opensearch.org/docs/latest

doc.quasar.ai/master

Developer

GridGain Systems, Inc.

DataJaguar, Inc.

Microsoft

Amazon Web Services

quasardb

Initial release

2007

2015

2010

2021

2009

Current release

GridGain 8.5.1

3.3 July 2023

V12

2.5.0, January 2023

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

Open Source

Apache Version 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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.

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Implementation language

Java, C++, .Net

C++

the server part. Clients available in other languages

C++

Java

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux

hosted

All OS with a Java VM

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

All search fields are automatically indexed

yes

with tags

SQL

Support of SQL

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-like query language

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP/JSON API

HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

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

Transact SQL

yes

Triggers

yes (cache interceptors and events)

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication

yes, with always 3 replicas available

yes

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

by using LevelDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

Security Hooks for custom implementations

rights management via user accounts

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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