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DBMS > Databricks vs. EXASOL vs. GeoSpock vs. Netezza

System Properties Comparison Databricks vs. EXASOL vs. GeoSpock vs. Netezza

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEXASOL  Xexclude from comparisonGeoSpock  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be 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.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Spatial and temporal data processing engine for extreme data scaleData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitewww.databricks.comwww.exasol.comgeospock.comwww.ibm.com/­products/­netezza
Technical documentationdocs.databricks.comwww.exasol.com/­resources
DeveloperDatabricksExasolGeoSpockIBM
Initial release201320002000
Current release2.0, September 2019
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, Javascript
Server operating systemshostedhostedLinux infoincluded in appliance
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnono
Secondary indexesyesyestemporal, categoricalyes
SQL infoSupport of SQLwith Databricks SQLyesANSI SQL for query only (using Presto)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
JDBCJDBC
ODBC
OLE DB
Supported programming languagesPython
R
Scala
Java
Lua
Python
R
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnoyes
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users can be defined per tableUsers with fine-grained authorization concept
More information provided by the system vendor
DatabricksEXASOLGeoSpockNetezza infoAlso called PureData System for Analytics by IBM
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEXASOLGeoSpockNetezza infoAlso called PureData System for Analytics by IBM
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