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DBMS > Amazon Neptune vs. Coveo vs. HEAVY.AI vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Coveo vs. HEAVY.AI vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCoveo  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Search engineRelational DBMSRelational DBMS
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
Score2.11
Rank#118  Overall
#11  Search engines
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunewww.coveo.comgithub.com/­heavyai/­heavydb
www.heavy.ai
splicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.coveo.comdocs.heavy.aisplicemachine.com/­how-it-works
DeveloperAmazonCoveoHEAVY.AI, Inc.Splice Machine
Initial release2017201220162014
Current release5.10, January 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAJava
Server operating systemshostedhostedLinuxLinux
OS X
Solaris
Windows
Data schemeschema-freehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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
SQL infoSupport of SQLnonoyesyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIJDBC
ODBC
Thrift
Vega
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
Java
JavaScript
Python
All languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnononoyes infoJava
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneyesSharding infoRound robinShared Nothhing Auto-Sharding, Columnar Partitioning
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.yesMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
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)granular access controls, API key management, content filtersfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneCoveoHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Splice Machine
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