DBMS > Cachelot.io vs. IBM Db2 Event Store vs. IBM Db2 warehouse vs. Ignite

System Properties Comparison Cachelot.io vs. IBM Db2 Event Store vs. IBM Db2 warehouse vs. Ignite

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Distributed Event Store optimized for Internet of Things use cases

Cloud-based data warehousing service

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Key-value store

Event Store
Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

cachelot.io

www.ibm.com/products/db2-event-store

www.ibm.com/products/db2/warehouse

ignite.apache.org

Technical documentation

www.ibm.com/docs/en/db2-event-store

apacheignite.readme.io/docs

Developer

IBM

Apache Software Foundation

Initial release

2015

2017

2014

2015

Current release

2.0

Apache Ignite 2.6

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

free developer edition available

commercial

Open Source

Apache 2.0

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

C++

C and C++

C++, Java, .Net

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

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

APIs and other access methods

Memcached protocol

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

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

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

PL/SQL, SQL PL

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

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-active shard replication

yes

yes (replicated cache)

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

none

Eventual Consistency

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

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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