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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonIRONdb  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.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 PlatformAn open source BigTable implementation based on distributed file systems such as HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelRelational DBMSDocument storeWide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Websitewww.datomic.comcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperCognitectGoogleHypertable Inc.Circonus LLC.
Initial release2012200820092017
Current release1.0.6735, June 20230.9.8.11, March 2016V0.10.20, January 2018
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++C and C++
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details herenoyes infotext, numeric, histograms
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 indexesyesyesrestricted infoonly exact value or prefix value scansno
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
HTTP API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Enginenoyes, in Lua
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 peersShardingShardingAutomatic, metric affinity per node
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 levelconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
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 ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
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)nono

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More resources
DatomicGoogle Cloud DatastoreHypertableIRONdb
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