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DBMS > Datomic vs. Google Cloud Datastore vs. NSDb vs. Titan

System Properties Comparison Datomic vs. Google Cloud Datastore vs. NSDb vs. Titan

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNSDb  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
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 PlatformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSDocument storeTime Series DBMSGraph 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
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websitewww.datomic.comcloud.google.com/­datastorensdb.iogithub.com/­thinkaurelius/­titan
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsnsdb.io/­Architecturegithub.com/­thinkaurelius/­titan/­wiki
DeveloperCognitectGoogleAurelius, owned by DataStax
Initial release2012200820172012
Current release1.0.7075, December 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2.0Open Source infoApache license, version 2.0
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, ClojureJava, ScalaJava
Server operating systemsAll OS with a Java VMhostedLinux
macOS
Linux
OS X
Unix
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyes: int, bigint, decimal, stringyes
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 indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC
HTTP REST
WebSocket
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Enginenoyes
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyes infovia Faunus, a graph analytics engine
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.Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graph
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)yesUsing Apache Luceneyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
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)User authentification and security via Rexster Graph Server

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More resources
DatomicGoogle Cloud DatastoreNSDbTitan
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