DBMS > Cachelot.io vs. EXASOL vs. Ignite vs. SWC-DB vs. Yanza

System Properties Comparison Cachelot.io vs. EXASOL vs. Ignite vs. SWC-DB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

In-memory caching system

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

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.

A high performance, scalable Wide Column DBMS

Time Series DBMS for IoT Applications

Primary database model

Key-value store

Relational DBMS

Key-value store
Relational DBMS

Wide column store

Time Series DBMS

Secondary database models

Time Series DBMS

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

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

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

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

cachelot.io

www.exasol.com

ignite.apache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

yanza.com

Technical documentation

www.exasol.com/resources

apacheignite.readme.io/docs

Developer

Exasol

Apache Software Foundation

Alex Kashirin

Yanza

Initial release

2015

2000

2015

2020

2015

Current release

Apache Ignite 2.6

0.5, April 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache 2.0

Open Source

GPL V3

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C++, Java, .Net

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Linux

Windows

Data scheme

schema-free

yes

schema-free

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

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

SQL-like query language

APIs and other access methods

Memcached protocol

.Net
JDBC
ODBC
WebSocket

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

Proprietary protocol
Thrift

HTTP API

Supported programming languages

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

Java
Lua
Python
R

C#
C++
Java
PHP
Python
Ruby
Scala

C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

yes (cache interceptors and events)

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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

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