DBMS > GridGain vs. OpenQM vs. RisingWave vs. Sequoiadb

System Properties Comparison GridGain vs. OpenQM vs. RisingWave vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

NewSQL database with distributed OLTP and SQL

Primary database model

Key-value store
Relational DBMS

Multivalue DBMS

Relational DBMS

Document store
Relational 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	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.gridgain.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.risingwave.com/database

www.sequoiadb.com

Technical documentation

www.gridgain.com/docs/index.html

docs.risingwave.com/docs/current/intro

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

GridGain Systems, Inc.

Rocket Software, originally Martin Phillips

RisingWave Labs

Sequoiadb Ltd.

Initial release

2007

1993

2022

2013

Current release

GridGain 8.5.1

3.4-12

1.2, September 2023

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Apache Version 2.0

Open Source

Server: AGPL; Client: Apache V2

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

Java, C++, .Net

Rust

C++

Server operating systems

Linux
OS X
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Docker
Linux
macOS

Linux

Data scheme

yes

with some exceptions

yes

schema-free

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

yes

oid, date, timestamp, binary, regex

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

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

yes

SQL-like query language

APIs and other access methods

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

JDBC
PostgreSQL wire protocol

proprietary protocol using JSON

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

Go
Java
JavaScript (Node.js)
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

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

yes

UDFs in Python or Java

JavaScript

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Document is locked during a transaction

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

User concepts

Access control

Security Hooks for custom implementations

Access rights can be defined down to the item level

Users and Roles

simple password-based access control

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More resources

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