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DBMS > Datomic vs. Kdb vs. Oracle Berkeley DB vs. RavenDB

System Properties Comparison Datomic vs. Kdb vs. Oracle Berkeley DB vs. RavenDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonKdb  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityHigh performance Time Series DBMSWidely used in-process key-value storeOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSTime Series DBMS
Vector DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document store
Secondary database modelsRelational DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitewww.datomic.comkx.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlravendb.net
Technical documentationdocs.datomic.comcode.kx.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlravendb.net/­docs
DeveloperCognitectKx Systems, a division of First Derivatives plcOracle infooriginally developed by Sleepycat, which was acquired by OracleHibernating Rhinos
Initial release20122000 infokdb was released 2000, kdb+ in 200319942010
Current release1.0.6735, June 20233.6, May 201818.1.40, May 20205.4, July 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infofree 32-bit versionOpen Source infocommercial license availableOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureqC, Java, C++ (depending on the Berkeley DB edition)C#
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.noyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyes infotable attribute 'grouped'yesyes
SQL infoSupport of SQLnoSQL-like query language (q)yes infoSQL interfaced based on SQLite is availableSQL-like query language (RQL)
APIs and other access methodsRESTful HTTP APIHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesClojure
Java
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functionsnoyes
TriggersBy using transaction functionsyes infowith viewsyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infosimilar paradigm used for internal processingnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 developmentyesyes
User concepts infoAccess controlnorights management via user accountsnoAuthorization levels configured per client per database
More information provided by the system vendor
DatomicKdbOracle Berkeley DBRavenDB
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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DatomicKdbOracle Berkeley DBRavenDB
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