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DBMS > Datomic vs. Google Cloud Bigtable vs. Manticore Search vs. RDF4J

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. Manticore Search vs. RDF4J

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonManticore Search  Xexclude from comparisonRDF4J infoformerly known as Sesame  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.Multi-storage database for search, including full-text search.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSKey-value store
Wide column store
Search engineRDF store
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.23
Rank#301  Overall
#21  Search engines
Score0.72
Rank#222  Overall
#9  RDF stores
Websitewww.datomic.comcloud.google.com/­bigtablemanticoresearch.comrdf4j.org
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docsmanual.manticoresearch.comrdf4j.org/­documentation
DeveloperCognitectGoogleManticore SoftwareSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2012201520172004
Current release1.0.7180, July 20246.0, February 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoGPL version 2Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Java
Server operating systemsAll OS with a Java VMhostedFreeBSD
Linux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-freeFixed schemayes infoRDF Schemas
Typing infopredefined data types such as float or dateyesnoInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XML
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query languageno
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnouser defined functionsyes
TriggersBy using transaction functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
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 zonesSynchronous replication based on Galera librarynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsyes infoisolated transactions for atomic changes and binary logging for safe writesACID infoIsolation support depends on the API used
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)yesyes infoThe original contents of fields are not stored in the Manticore index.yes infoin-memory storage is supported as well
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)nono

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More resources
DatomicGoogle Cloud BigtableManticore SearchRDF4J infoformerly known as Sesame
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