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DBMS > Amazon Neptune vs. Ingres vs. Microsoft Access vs. Microsoft Azure Synapse Analytics vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Ingres vs. Microsoft Access vs. Microsoft Azure Synapse Analytics vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudWell established RDBMSMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSRelational DBMSRelational 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
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunewww.actian.com/­databases/­ingreswww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­synapse-analyticssplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.actian.com/­ingresdeveloper.microsoft.com/­en-us/­accessdocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-works
DeveloperAmazonActian CorporationMicrosoftMicrosoftSplice Machine
Initial release20171974 infooriginally developed at University Berkely in early 1970s199220162014
Current release11.2, May 20221902 (16.0.11328.20222), March 20193.1, March 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C++Java
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Windows infoNot a real database server, but making use of DLLshostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
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.nono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoyesyes infobut not compliant to any SQL standardyesyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyes infosince Access 2010 using the ACE-engineTransact SQLyes infoJava
Triggersnoyesyes infosince Access 2010 using the ACE-enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoIngres Star to access multiple databases simultaneouslynoneSharding, horizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
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.Ingres ReplicatornoneyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infobut no files for transaction loggingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003yesAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneIngresMicrosoft AccessMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice Machine
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