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

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

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonH2  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA 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 Database
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSDocument store
Secondary database modelsSpatial DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
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
Websitewww.datomic.comcloud.google.com/­spannerwww.h2database.comazure.microsoft.com/­services/­synapse-analyticsravendb.net
Technical documentationdocs.datomic.comcloud.google.com/­spanner/­docswww.h2database.com/­html/­main.htmldocs.microsoft.com/­azure/­synapse-analyticsravendb.net/­docs
DeveloperCognitectGoogleThomas MuellerMicrosoftHibernating Rhinos
Initial release20122017200520162010
Current release1.0.6735, June 20232.2.220, July 20235.4, July 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaC++C#
Server operating systemsAll OS with a Java VMhostedAll OS with a Java VMhostedLinux
macOS
Raspberry Pi
Windows
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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 indexesyesyesyesyesyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011yesyesSQL-like query language (RQL)
APIs and other access methodsRESTful HTTP APIgRPC (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
Supported programming languagesClojure
Java
Go
Java
JavaScript (Node.js)
Python
JavaC#
Java
PHP
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoJava Stored Procedures and User-Defined FunctionsTransact SQLyes
TriggersBy using transaction functionsnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnoneSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication with 3 replicas for regional instances.With clustering: 2 database servers on different computers operate on identical copies of a databaseyesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integritynoyes 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 dataACIDACID infoStrict serializable isolationACIDACIDACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlnoAccess 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 database

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More resources
DatomicGoogle Cloud SpannerH2Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRavenDB
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