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DBMS > Apache IoTDB vs. HEAVY.AI vs. Microsoft Azure AI Search vs. Sphinx vs. TerminusDB

System Properties Comparison Apache IoTDB vs. HEAVY.AI vs. Microsoft Azure AI Search vs. Sphinx vs. TerminusDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databasesScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelTime Series DBMSRelational DBMSSearch engineSearch engineGraph DBMS
Secondary database modelsSpatial DBMSVector DBMSDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Score0.23
Rank#316  Overall
#27  Graph DBMS
Websiteiotdb.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­en-us/­services/­searchsphinxsearch.comterminusdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.heavy.ailearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docsterminusdb.github.io/­terminusdb/­#
DeveloperApache Software FoundationHEAVY.AI, Inc.MicrosoftSphinx Technologies Inc.DataChemist Ltd.
Initial release20182016201520012018
Current release1.1.0, April 20235.10, January 2022V13.5.1, February 202311.0.0, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ and CUDAC++Prolog, Rust
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nononono
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like query language (SphinxQL)SQL-like query language (WOQL)
APIs and other access methodsJDBC
Native API
JDBC
ODBC
Thrift
Vega
RESTful HTTP APIProprietary protocolOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript
Python
Server-side scripts infoStored proceduresyesnononoyes
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoRound robinSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationyes infoImplicit feature of the cloud servicenoneJournaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyes infousing Azure authenticationnoRole-based access control

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More resources
Apache IoTDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure AI SearchSphinxTerminusDB infoformer name was DataChemist
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