DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Ignite vs. IRONdb vs. Linter vs. TimescaleDB

System Properties Comparison Ignite vs. IRONdb vs. Linter vs. TimescaleDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonIRONdb  Xexclude from comparisonLinter  Xexclude from comparisonTimescaleDB  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionApache 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 simplicityRDBMS for high security requirementsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value store
Relational DBMS
Time Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteignite.apache.orgwww.circonus.com/solutions/time-series-database/linter.ruwww.timescale.com
Technical documentationapacheignite.readme.io/­docsdocs.circonus.com/irondb/category/getting-starteddocs.timescale.com
DeveloperApache Software FoundationCirconus LLC.relex.ruTimescale
Initial release2015201719902017
Current releaseApache Ignite 2.6V0.10.20, January 20182.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetC and C++C and C++C
Server operating systemsLinux
OS X
Solaris
Windows
LinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like query language (Circonus Analytics Query Language: CAQL)yesyes infofull PostgreSQL SQL syntax
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP APIADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
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
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes, in Luayes infoproprietary syntax with the possibility to convert from PL/SQLuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes (cache interceptors and events)noyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)configurable replication factor, datacenter awareSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlSecurity Hooks for custom implementationsnofine grained access rights according to SQL-standardfine 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
IgniteIRONdbLinterTimescaleDB
Recent citations in the news

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

Apache Ignite: An Overview
6 September 2023, Open Source For You

GridGain Releases Conference Schedule for Virtual Apache Ignite Summit 2023
1 June 2023, Datanami

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

СУБД «Линтер Бастион» прошла сертификацию ФСТЭК России по новым требованиям к системам управления ...
11 March 2024, ServerNews

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Present your product here