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DBMS > Datomic vs. GeoSpock vs. Google Cloud Datastore vs. Hypertable

System Properties Comparison Datomic vs. GeoSpock vs. Google Cloud Datastore vs. Hypertable

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpatial and temporal data processing engine for extreme data scaleAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelRelational DBMSRelational DBMSDocument storeWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websitewww.datomic.comgeospock.comcloud.google.com/­datastore
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docs
DeveloperCognitectGeoSpockGoogleHypertable Inc.
Initial release201220082009
Current release1.0.6735, June 20232.0, September 20190.9.8.11, March 2016
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoGNU version 3. Commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava, JavascriptC++
Server operating systemsAll OS with a Java VMhostedhostedLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereno
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 indexesyestemporal, categoricalyesrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)SQL-like query language (GQL)no
APIs and other access methodsRESTful HTTP APIJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsnousing Google App Engineno
TriggersBy using transaction functionsnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersAutomatic shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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 can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
DatomicGeoSpockGoogle Cloud DatastoreHypertable
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