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DBMS > GeoSpock vs. HEAVY.AI vs. Oracle Berkeley DB vs. Riak KV

System Properties Comparison GeoSpock vs. HEAVY.AI vs. Oracle Berkeley DB vs. Riak KV

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionSpatial and temporal data processing engine for extreme data scaleA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareWidely used in-process key-value storeDistributed, fault tolerant key-value store
Primary database modelRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Key-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsTime Series DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#299  Overall
#138  Relational DBMS
Score1.29
Rank#153  Overall
#73  Relational DBMS
Score2.77
Rank#109  Overall
#20  Key-value stores
#3  Native XML DBMS
Score6.63
Rank#64  Overall
#8  Key-value stores
Websitegeospock.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.oracle.com/­technetwork/­database/­database-technologies/­berkeleydb/­overview/­index.htmlriak.com/­products/­riak-kv
Technical documentationdocs.geospock.com/­Content/­Home.htmdocs.heavy.aidocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperGeoSpockHEAVY.AI, Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleBasho Technologies
Initial release201619942009
Current release2.0, September 20195.10, January 202218.1.40, May 20202.1.0, April 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infocommercial license availableOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptC++ and CUDAC, Java, C++ (depending on the Berkeley DB edition)Erlang
Server operating systemshostedLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.nonoyes infoonly with the Berkeley DB XML editionno
Secondary indexestemporal, categoricalnoyesrestricted
SQL infoSupport of SQLANSI SQL for query only (using Presto)yesyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsJDBCJDBC
ODBC
Thrift
Vega
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnononoJavaScript and Erlang
Triggersnonoyes infoonly for the SQL APIyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoRound robinnoneSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyesyes
User concepts infoAccess controlAccess rights for users can be defined per tablefine grained access rights according to SQL-standardnono
More information provided by the system vendor
GeoSpockHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Oracle Berkeley DBRiak KV
Specific characteristicsOptimizes memory and compute layers to deliver unprecedented performance. Natively...
» more
Competitive advantagesOnly HEAVY.AI allows users to visually and interactively discover high-value patterns,...
» more
Typical application scenariosAdvanced analytics, geospatial and time-series analytics, accelerated data science,...
» more
Licensing and pricing modelsHEAVY.AI Free (Free Forever), Foundations ($2k/month), and Enterprise Licensure (Inquire...
» more

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More resources
GeoSpockHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Oracle Berkeley DBRiak KV
Recent citations in the news

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

Cambridge-Based GeoSpock Secures £10 Million Additional Funding
8 January 2019, Business Wire

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2 October 2020, EU-Startups

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GeoSpock showcases rapid expansion with data insights
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