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DBMS > Databricks vs. Datomic vs. Drizzle

System Properties Comparison Databricks vs. Datomic vs. Drizzle

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonDrizzle  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Websitewww.databricks.comwww.datomic.com
Technical documentationdocs.databricks.comdocs.datomic.com
DeveloperDatabricksCognitectDrizzle project, originally started by Brian Aker
Initial release201320122008
Current release1.0.6735, June 20237.2.4, September 2012
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoGNU GPL
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
OS X
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes
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.yesno
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
Supported programming languagesPython
R
Scala
Clojure
Java
C
C++
Java
PHP
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoTransaction Functionsno
TriggersBy using transaction functionsno infohooks for callbacks inside the server can be used.
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 nodesyesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes 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.noyes inforecommended only for testing and development
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTP
More information provided by the system vendor
DatabricksDatomicDrizzle
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDatomicDrizzle
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