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DBMS > Amazon Neptune vs. Google Cloud Spanner vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Google Cloud Spanner vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonIngres  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 cloudA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Well established RDBMSElastic, 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
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­spannerwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticssplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­spanner/­docsdocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-works
DeveloperAmazonGoogleActian CorporationMicrosoftSplice Machine
Initial release201720171974 infooriginally developed at University Berkely in early 1970s20162014
Current release11.2, May 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++Java
Server operating systemshostedhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
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.nonono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011yesyesyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
C#
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesTransact SQLyes infoJava
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, 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.Multi-source replication with 3 replicas for regional instances.Ingres ReplicatoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno 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 dataACIDACID infoStrict serializable isolationACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes, multi-version concurrency control (MVCC)
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.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneGoogle Cloud SpannerIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice Machine
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