DBMS > GridGain vs. NSDb vs. OpenQM vs. SwayDB

System Properties Comparison GridGain vs. NSDb vs. OpenQM vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Multivalue DBMS

Key-value store

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
	#41	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.gridgain.com

nsdb.io

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

swaydb.simer.au

Technical documentation

www.gridgain.com/docs/index.html

nsdb.io/Architecture

Developer

GridGain Systems, Inc.

Rocket Software, originally Martin Phillips

Simer Plaha

Initial release

2007

2017

1993

2018

Current release

GridGain 8.5.1

3.4-12

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

Open Source

GNU Affero GPL V3.0

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

Java, Scala

Scala

Server operating systems

Linux
OS X
Solaris
Windows

Linux
macOS

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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 fields are automatically indexed

yes

SQL

Support of SQL

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

SQL-like query language

APIs and other access methods

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

gRPC
HTTP REST
WebSocket

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Java
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

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

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

none

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

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More resources

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