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DBMS > Amazon Neptune vs. Datomic vs. Microsoft Azure Table Storage vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Datomic vs. Microsoft Azure Table Storage vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatomic  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSWide column storeRelational 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
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.datomic.comazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonCognitectMicrosoftApache Software Foundation
Initial release2017201220122014
Current release1.0.7075, December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScala
Server operating systemshostedAll OS with a Java VMhostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
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.nononono
Secondary indexesnoyesnono
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIRESTful HTTP APIJDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
Java
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnono
TriggersnoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud serviceyes, 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.none infoBut extensive use of caching in the application peersyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights based on private key authentication or shared access signaturesno

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More resources
Amazon NeptuneDatomicMicrosoft Azure Table StorageSpark SQL
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