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DBMS > HEAVY.AI vs. Lovefield vs. Oracle Berkeley DB vs. PlanetScale

System Properties Comparison HEAVY.AI vs. Lovefield vs. Oracle Berkeley DB vs. PlanetScale

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPlanetScale  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEmbeddable relational database for web apps written in pure JavaScriptWidely used in-process key-value storeScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score0.22
Rank#306  Overall
#138  Relational DBMS
Score1.88
Rank#130  Overall
#23  Key-value stores
#3  Native XML DBMS
Score1.09
Rank#178  Overall
#82  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlplanetscale.com
Technical documentationdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlplanetscale.com/­docs
DeveloperHEAVY.AI, Inc.GoogleOracle infooriginally developed by Sleepycat, which was acquired by OraclePlanetScale
Initial release2016201419942020
Current release5.10, January 20222.1.12, February 201718.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infocommercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAJavaScriptC, Java, C++ (depending on the Berkeley DB edition)Go
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Docker
Linux
macOS
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 edition
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesSQL-like query language infovia JavaScript builder patternyes infoSQL interfaced based on SQLite is availableyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
JavaScript.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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnononoyes infoproprietary syntax
TriggersnoUsing read-only observersyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDByesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoUsers with fine-grained authorization concept infono user groups or roles

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldOracle Berkeley DBPlanetScale
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