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

DBMS > Ignite vs. InfinityDB vs. MonetDB vs. Splice Machine vs. TimescaleDB

System Properties Comparison Ignite vs. InfinityDB vs. MonetDB vs. Splice Machine vs. TimescaleDB

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonInfinityDB  Xexclude from comparisonMonetDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimescaleDB  Xexclude from comparison
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 Java embedded Key-Value Store which extends the Java Map interfaceA relational database management system that stores data in columnsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value store
Relational DBMS
Key-value storeRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteignite.apache.orgboilerbay.comwww.monetdb.orgsplicemachine.comwww.timescale.com
Technical documentationapacheignite.readme.io/­docsboilerbay.com/­infinitydb/­manualwww.monetdb.org/­Documentationsplicemachine.com/­how-it-worksdocs.timescale.com
DeveloperApache Software FoundationBoiler Bay Inc.MonetDB BVSplice MachineTimescale
Initial release20152002200420142017
Current releaseApache Ignite 2.64.0Dec2023 (11.49), December 20233.1, March 20212.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoMozilla Public License 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetJavaCJavaC
Server operating systemsLinux
OS X
Solaris
Windows
All OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyesyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyesnumerics, 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.yesnoyes
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoyes infoSQL 2003 with some extensionsyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
JavaC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.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)noyes, in SQL, C, Ryes infoJavauser 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)noyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding via remote tablesShared Nothhing Auto-Sharding, Columnar Partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)nonenone infoSource-replica replication available in experimental statusMulti-source replication
Source-replica replication
Source-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)nonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsnofine grained access rights according to SQL-standardAccess rights for users, groups and roles 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
IgniteInfinityDBMonetDBSplice MachineTimescaleDB
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

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

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

provided by Google News

In 2024 the MonetDB Foundation was established for the preservation, maintenance and further development of the ...
31 January 2024, Centrum Wiskunde & Informatica (CWI)

MonetDB Secures Investment From (and Partners With) ServiceNow
9 December 2021, Datanami

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R - Part I - DataScienceCentral.com
6 April 2018, Data Science Central

How MonetDB Exploits Modern CPU Performance | by Dwi Prasetyo Adi Nugroho
14 January 2020, Towards Data Science

ServiceNow ordered a year's worth of hardware to avoid supply chain hassles
25 May 2022, The Register

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

New Splice Machine RDBMS unites OLTP and OLAP
18 November 2015, CIO

Big Data News: Splice Machine, Carpathia, Altiscale, DataGravity
11 February 2014, Data Center Knowledge

How To Axe Db2 But Keep Your Code
10 March 2020, Towards Data Science

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

Timescale announces $15M investment and new enterprise version of TimescaleDB
29 January 2019, TechCrunch

provided by Google News



Share this page

Featured Products

Milvus logo

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

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

Neo4j logo

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

Present your product here