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DBMS > Amazon Neptune vs. Apache IoTDB vs. HEAVY.AI vs. Sphinx

System Properties Comparison Amazon Neptune vs. Apache IoTDB vs. HEAVY.AI vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAn 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 hardwareOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­neptuneiotdb.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
sphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.heavy.aisphinxsearch.com/­docs
DeveloperAmazonApache Software FoundationHEAVY.AI, Inc.Sphinx Technologies Inc.
Initial release2017201820162001
Current release1.1.0, April 20235.10, January 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++ and CUDAC++
Server operating systemshostedAll OS with a Java VM (>= 1.8)LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
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.nonono
Secondary indexesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageyesSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native API
JDBC
ODBC
Thrift
Vega
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoRound robinSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesfine grained access rights according to SQL-standardno

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More resources
Amazon NeptuneApache IoTDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Sphinx
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