DBMS > EXASOL vs. GridGain vs. IBM Db2 vs. Riak KV vs. Snowflake

System Properties Comparison EXASOL vs. GridGain vs. IBM Db2 vs. Riak KV vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Distributed, fault tolerant key-value store

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

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

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.exasol.com

www.gridgain.com

www.ibm.com/products/db2

www.snowflake.com

Technical documentation

www.exasol.com/resources

www.gridgain.com/docs/index.html

www.ibm.com/docs/en/db2

www.tiot.jp/riak-docs/riak/kv/latest

docs.snowflake.net/manuals/index.html

Developer

Exasol

GridGain Systems, Inc.

IBM

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2000

2007

1983

host version

2009

2014

Current release

GridGain 8.5.1

12.1, October 2016

3.2.0, December 2022

License

Commercial or Open Source

commercial

free version is available

Open Source

Apache version 2, commercial enterprise edition

commercial

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.

Implementation language

Java, C++, .Net

C and C++

Erlang

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

restricted

SQL

Support of SQL

yes

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

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

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

yes

Erlang

user defined functions

Triggers

yes

yes (cache interceptors and events)

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

no "single point of failure"

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

with separate tools (MQ, InfoSphere)

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

yes, using Riak Security

Users with fine-grained authorization concept, user roles and pluggable authentication

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