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DBMS > Amazon Neptune vs. HEAVY.AI vs. jBASE vs. Kinetica vs. LevelDB

System Properties Comparison Amazon Neptune vs. HEAVY.AI vs. jBASE vs. Kinetica vs. LevelDB

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparisonLevelDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUsEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelGraph DBMS
RDF store
Relational DBMSMultivalue DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Websiteaws.amazon.com/­neptunegithub.com/­heavyai/­heavydb
www.heavy.ai
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.comgithub.com/­google/­leveldb
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.heavy.aidocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperAmazonHEAVY.AI, Inc.Rocket Software (formerly Zumasys)KineticaGoogle
Initial release20172016199120122011
Current release5.10, January 20225.77.1, August 20211.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC, C++C++
Server operating systemshostedLinuxAIX
Linux
Windows
LinuxIllumos
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesoptionalyesno
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.nonoyesnono
Secondary indexesnonoyesno
SQL infoSupport of SQLnoyesEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresnonoyesuser defined functionsno
Triggersnonoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoRound robinShardingShardingnone
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.Multi-source replicationyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAccess rights for users and roles on table levelno

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More resources
Amazon NeptuneHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022jBASEKineticaLevelDB
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