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DBMS > Datomic vs. Google Cloud Datastore vs. IRONdb vs. Microsoft Azure Synapse Analytics

System Properties Comparison Datomic vs. Google Cloud Datastore vs. IRONdb vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Websitewww.datomic.comcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­azure/­synapse-analytics
DeveloperCognitectGoogleCirconus LLC.Microsoft
Initial release2012200820172016
Current release1.0.7075, December 2023V0.10.20, January 2018
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC and C++C++
Server operating systemsAll OS with a Java VMhostedLinuxhosted
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyes infotext, numeric, histogramsyes
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 indexesyesyesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)yes
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIADO.NET
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
Java
PHP
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engineyes, in LuaTransact SQL
TriggersBy using transaction functionsCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingAutomatic, metric affinity per nodeSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosconfigurable replication factor, datacenter awareyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
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 developmentnono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes

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More resources
DatomicGoogle Cloud DatastoreIRONdbMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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