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DBMS > GeoSpock vs. Heroic vs. OpenQM vs. TimescaleDB vs. Valentina Server

System Properties Comparison GeoSpock vs. Heroic vs. OpenQM vs. TimescaleDB vs. Valentina Server

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHeroic  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonTimescaleDB  Xexclude from comparisonValentina Server  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchQpenQM is a high-performance, self-tuning, multi-value DBMSA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLObject-relational database and reports server
Primary database modelRelational DBMSTime Series DBMSMultivalue DBMSTime Series DBMSRelational DBMS
Secondary database modelsTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitegeospock.comgithub.com/­spotify/­heroicwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.timescale.comwww.valentina-db.net
Technical documentationspotify.github.io/­heroicdocs.timescale.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperGeoSpockSpotifyRocket Software, originally Martin PhillipsTimescaleParadigma Software
Initial release2014199320171999
Current release2.0, September 20193.4-122.15.0, May 20245.7.5
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPLv2, extended commercial license availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJavaC
Server operating systemshostedAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes infowith some exceptionsyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyesyes
Secondary indexestemporal, categoricalyes infovia Elasticsearchyesyesyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)nonoyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsJDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ODBC
Supported programming languages.Net
Basic
C
Java
Objective C
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnonoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersnonoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingyesyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononoyes
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights can be defined down to the item levelfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
GeoSpockHeroicOpenQM infoalso called QMTimescaleDBValentina Server
Recent citations in the news

Cambridge-based data analytics startup GeoSpock lands €4.6 million
2 October 2020, EU-Startups

nChain leads investment round in extreme-scale data firm GeoSpock
2 October 2020, CoinGeek

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

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6 October 2020, Tech in Asia

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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, businesswire.com

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

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A Look at Valentina — SitePoint
18 April 2014, SitePoint

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7 December 2018, H2S Media

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