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

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

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatomic  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  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 datasetsApplication development environment with integrated database management systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSWide column storeRelational DBMSRelational 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.datomic.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgespark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.datomic.comdocumentation.progress.com/­output/­ua/­OpenEdge_latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonCognitectMicrosoftProgress Software CorporationApache Software Foundation
Initial release20172012201219842014
Current release1.0.6735, June 2023OpenEdge 12.2, March 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScala
Server operating systemshostedAll OS with a Java VMhostedAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononoyesno
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLnononoyes infoclose to SQL 92SQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIRESTful HTTP APIJDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
Java
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language)Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnoyesno
TriggersnoBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4yes, 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.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
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 developmentnonono
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 signaturesUsers and groupsno

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More resources
Amazon NeptuneDatomicMicrosoft Azure Table StorageOpenEdgeSpark SQL
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