DBMS > 4D vs. GridGain vs. Kinetica vs. TimesTen

System Properties Comparison 4D vs. GridGain vs. Kinetica vs. TimesTen

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Fully vectorized database across both GPUs and CPUs

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.4d.com

www.gridgain.com

www.kinetica.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

developer.4d.com

www.gridgain.com/docs/index.html

docs.kinetica.com

docs.oracle.com/database/timesten-18.1

Developer

4D, Inc

GridGain Systems, Inc.

Kinetica

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1984

2007

2012

1998

Current release

v20, April 2023

GridGain 8.5.1

7.1, August 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

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

C, C++

Server operating systems

OS X
Windows

Linux
OS X
Solaris
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

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

SQL-like DML and DDL statements

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

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

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

4D proprietary IDE
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

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

user defined functions

PL/SQL

Triggers

yes

yes (cache interceptors and events)

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes (replicated cache)

Source-replica replication

Multi-source replication
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

Immediate Consistency or Eventual Consistency depending on configuration

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 means of logfiles and checkpoints

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Users and groups

Security Hooks for custom implementations

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

GridGain to Sponsor and Speak at Three Key Industry Events in May 2024
2 May 2024, PR Newswire

GridGain's 2023 Growth Positions Company for Strong 2024
25 January 2024, Datanami

GridGain Named in the 2023 Gartner® Market Guide for Event Stream Processing
22 August 2023, GlobeNewswire

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain Adds Andy Sacks as Chief Revenue Officer, Promotes Lalit Ahuja to Chief Customer and Product Officer ...
17 July 2023, Yahoo Finance

provided by Google News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News

In-memory databases with Emulex Gen 7
25 October 2023, Broadcom Inc.

The Intel Xeon E7-8800 v3 Review: The POWER8 Killer?
8 May 2015, AnandTech

provided by Google News

Share this page