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DBMS > Databricks vs. EXASOL vs. Splice Machine

System Properties Comparison Databricks vs. EXASOL vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEXASOL  Xexclude from comparisonSplice Machine  Xexclude from comparison
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.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
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
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.databricks.comwww.exasol.comsplicemachine.com
Technical documentationdocs.databricks.comwww.exasol.com/­resourcessplicemachine.com/­how-it-works
DeveloperDatabricksExasolSplice Machine
Initial release201320002014
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedLinux
OS X
Solaris
Windows
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 SQLyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
JDBC
Native Spark Datasource
ODBC
Supported programming languagesPython
R
Scala
Java
Lua
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyes infoJava
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksEXASOLSplice Machine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEXASOLSplice Machine
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