DBMS > Ignite vs. IRONdb vs. Warp 10

System Properties Comparison Ignite vs. IRONdb vs. Warp 10

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Editorial information provided by DB-Engines

Name

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

Description

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 distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

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

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

ignite.apache.org

www.circonus.com/solutions/time-series-database/

www.warp10.io

Technical documentation

apacheignite.readme.io/docs

docs.circonus.com/irondb/category/getting-started

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation

Circonus LLC.

SenX

Initial release

2015

2017

2015

Current release

Apache Ignite 2.6

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

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

C++, Java, .Net

C and C++

Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

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

HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

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

yes, in Lua

yes

WarpScript

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

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 per node, eventual consistency across nodes

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

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

Security Hooks for custom implementations

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

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