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DBMS > Amazon Neptune vs. Microsoft Azure Table Storage vs. Realm vs. Splice Machine vs. Teradata Aster

System Properties Comparison Amazon Neptune vs. Microsoft Azure Table Storage vs. Realm vs. Splice Machine vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRealm  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionFast, reliable graph database built for the cloudA Wide Column Store for rapid development using massive semi-structured datasetsA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPlatform for big data analytics on multistructured data sources and types
Primary database modelGraph DBMS
RDF store
Wide column storeDocument 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
Score4.48
Rank#75  Overall
#6  Wide column stores
Score7.60
Rank#52  Overall
#9  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­neptuneazure.microsoft.com/­en-us/­services/­storage/­tablesrealm.iosplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesrealm.io/­docssplicemachine.com/­how-it-works
DeveloperAmazonMicrosoftRealm, acquired by MongoDB in May 2019Splice MachineTeradata
Initial release20172012201420142005
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.nononoyes infoin Aster File Store
Secondary indexesnonoyesyesyes
SQL infoSupport of SQLnononoyesyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonono inforuns within the applications so server-side scripts are unnecessaryyes infoJavaR packages
Triggersnonoyes infoChange Listenersyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicenoneShared Nothhing Auto-Sharding, Columnar PartitioningSharding
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.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoIn-Memory realmyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesyesAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Amazon NeptuneMicrosoft Azure Table StorageRealmSplice MachineTeradata Aster
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