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DBMS > Google Cloud Spanner vs. H2 vs. Microsoft Azure Synapse Analytics vs. RavenDB vs. RDF4J

System Properties Comparison Google Cloud Spanner vs. H2 vs. Microsoft Azure Synapse Analytics vs. RavenDB vs. RDF4J

Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonH2  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRavenDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA 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.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeRDF store
Secondary database modelsSpatial DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­spannerwww.h2database.comazure.microsoft.com/­services/­synapse-analyticsravendb.netrdf4j.org
Technical documentationcloud.google.com/­spanner/­docswww.h2database.com/­html/­main.htmldocs.microsoft.com/­azure/­synapse-analyticsravendb.net/­docsrdf4j.org/­documentation
DeveloperGoogleThomas MuellerMicrosoftHibernating RhinosSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20172005201620102004
Current release2.2.220, July 20235.4, July 2022
License infoCommercial or Open SourcecommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C#Java
Server operating systemshostedAll OS with a Java VMhostedLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyesnoyes
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
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011yesyesSQL-like query language (RQL)no
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
JavaC#
Java
PHP
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresnoJava Stored Procedures and User-Defined FunctionsTransact SQLyesyes
Triggersnoyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding, horizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.With clustering: 2 database servers on different computers operate on identical copies of a databaseyesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integrityyes 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-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationACIDACIDACID, Cluster-wide transaction availableACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
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, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesAuthorization levels configured per client per databaseno

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More resources
Google Cloud SpannerH2Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRavenDBRDF4J infoformerly known as Sesame
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