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DBMS > Amazon Neptune vs. Kinetica vs. Spark SQL vs. YottaDB

System Properties Comparison Amazon Neptune vs. Kinetica vs. Spark SQL vs. YottaDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingA fast and solid embedded Key-value store
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websiteaws.amazon.com/­neptunewww.kinetica.comspark.apache.org/­sqlyottadb.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlyottadb.com/­resources/­documentation
DeveloperAmazonKineticaApache Software FoundationYottaDB, LLC
Initial release2017201220142001
Current release7.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaC
Server operating systemshostedLinuxLinux
OS X
Windows
Docker
Linux
Data schemeschema-freeyesyesschema-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.nononono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statementsby using the Octo plugin
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresnouser defined functionsno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
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.Source-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and roles on table levelnoUsers and groups based on OS-security mechanisms

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More resources
Amazon NeptuneKineticaSpark SQLYottaDB
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