DBMS > GridGain vs. SAP IQ vs. STSdb vs. XTDB

System Properties Comparison GridGain vs. SAP IQ vs. STSdb vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

Columnar RDBMS optimized for Big Data analytics

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

Relational DBMS

column-oriented

Key-value store

Document store

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.gridgain.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

github.com/STSSoft/STSdb4

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.gridgain.com/docs/index.html

help.sap.com/docs/SAP_IQ

www.xtdb.com/docs

Developer

GridGain Systems, Inc.

SAP, formerly Sybase

STS Soft SC

Juxt Ltd.

Initial release

2007

1994

2011

2019

Current release

GridGain 8.5.1

16.1 SPS04, April 2019

4.0.8, September 2015

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

Open Source

MIT License

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

Clojure

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

.NET Client API

HTTP REST
JDBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

C#
Java

Clojure
Java

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

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

SAP/Sybase Replication Server

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

fine grained access rights according to SQL-standard

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