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DBMS > Graph Engine vs. Microsoft Azure Table Storage vs. RavenDB vs. SAP Adaptive Server vs. Spark SQL

System Properties Comparison Graph Engine vs. Microsoft Azure Table Storage vs. RavenDB vs. SAP Adaptive Server vs. Spark SQL

Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRavenDB  Xexclude from comparisonSAP Adaptive Server infoformer name: Sybase ASE  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA Wide Column Store for rapid development using massive semi-structured datasetsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseThe SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
Key-value store
Wide column storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Spatial DBMS infowith Boeing's Spatial Query Server
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.92
Rank#101  Overall
#18  Document stores
Score36.31
Rank#25  Overall
#17  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.graphengine.ioazure.microsoft.com/­en-us/­services/­storage/­tablesravendb.netwww.sap.com/­products/­technology-platform/­sybase-ase.htmlspark.apache.org/­sql
Technical documentationwww.graphengine.io/­docs/­manualravendb.net/­docshelp.sap.com/­docs/­SAP_ASEspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftMicrosoftHibernating RhinosSAP, SybaseApache Software Foundation
Initial release20102012201019872014
Current release5.4, July 202216.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoAGPL version 3, commercial license availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CC#C and C++Scala
Server operating systems.NEThostedLinux
macOS
Raspberry Pi
Windows
AIX
HP-UX
Linux
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnonoSQL-like query language (RQL)yesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIRESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languagesC#
C++
F#
Visual Basic
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Cobol
Java
Java
Perl
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyesJava and Transact-SQLno
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACID, Cluster-wide transaction availableACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesAuthorization levels configured per client per databasefine grained access rights according to SQL-standardno

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More resources
Graph Engine infoformer name: TrinityMicrosoft Azure Table StorageRavenDBSAP Adaptive Server infoformer name: Sybase ASESpark SQL
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