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DBMS > GeoSpock vs. Graphite vs. Rockset vs. Ultipa

System Properties Comparison GeoSpock vs. Graphite vs. Rockset vs. Ultipa

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGraphite  Xexclude from comparisonRockset  Xexclude from comparisonUltipa  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 scaleData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperA scalable, reliable search and analytics service in the cloud, built on RocksDBHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelRelational DBMSTime Series DBMSDocument storeGraph DBMS
Secondary database modelsTime Series DBMSRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score0.13
Rank#335  Overall
#31  Graph DBMS
Websitegeospock.comgithub.com/­graphite-project/­graphite-webrockset.comwww.ultipa.com
Technical documentationgraphite.readthedocs.iodocs.rockset.comwww.ultipa.com/­document
DeveloperGeoSpockChris DavisRocksetUltipa
Initial release200620192019
Current release2.0, September 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptPythonC++
Server operating systemshostedLinux
Unix
hosted
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesNumeric data onlydynamic typing
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.nonono infoingestion from XML files supported
Secondary indexestemporal, categoricalnoall fields are automatically indexed
SQL infoSupport of SQLANSI SQL for query only (using Presto)noRead-only SQL queries, including JOINs
APIs and other access methodsJDBCHTTP API
Sockets
HTTP RESTRESTful HTTP API
Supported programming languagesJavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users can be defined per tablenoAccess rights for users and organizations can be defined via Rockset console

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More resources
GeoSpockGraphiteRocksetUltipa
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Recent citations in the news

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

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, AlexaBlockchain

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
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The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
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23 January 2015, InfoQ.com

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