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DBMS > Datomic vs. Google Cloud Bigtable vs. ReductStore

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. ReductStore

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonReductStore  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websitewww.datomic.comcloud.google.com/­bigtablegithub.com/­reductstore
www.reduct.store
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docswww.reduct.store/­docs
DeveloperCognitectGoogleReductStore LLC
Initial release201220152023
Current release1.0.7075, December 20231.9, March 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++, Rust
Server operating systemsAll OS with a Java VMhostedDocker
Linux
macOS
Windows
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesno
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.nono
Secondary indexesyesno
SQL infoSupport of SQLnono
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyes infoTransaction Functionsno
TriggersBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
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 developmentno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
DatomicGoogle Cloud BigtableReductStore
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