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DBMS > atoti vs. HEAVY.AI vs. Lovefield vs. Microsoft Azure AI Search vs. Oracle Berkeley DB

System Properties Comparison atoti vs. HEAVY.AI vs. Lovefield vs. Microsoft Azure AI Search vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A 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 JavaScriptSearch-as-a-service for web and mobile app developmentWidely used in-process key-value store
Primary database modelObject oriented DBMSRelational DBMSRelational DBMSSearch engineKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsSpatial DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websiteatoti.iogithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldazure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.atoti.iodocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdlearn.microsoft.com/­en-us/­azure/­searchdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperActiveViamHEAVY.AI, Inc.GoogleMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2016201420151994
Current release5.10, January 20222.1.12, February 2017V118.1.40, May 2020
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0commercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ and CUDAJavaScriptC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesnoyesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)yesSQL-like query language infovia JavaScript builder patternnoyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
ODBC
Thrift
Vega
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
JavaScriptC#
Java
JavaScript
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
Server-side scripts infoStored proceduresPythonnononono
TriggersnoUsing read-only observersnoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding infoRound robinnoneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneyes infoImplicit feature of the cloud serviceSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
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.yesyesyes infousing MemoryDBnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyes infousing Azure authenticationno

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More resources
atotiHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldMicrosoft Azure AI SearchOracle Berkeley DB
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