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DBMS > Databricks vs. InterSystems Caché vs. Netezza vs. SpaceTime

System Properties Comparison Databricks vs. InterSystems Caché vs. Netezza vs. SpaceTime

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpaceTime  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed 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.A multi-model DBMS and application serverData warehouse and analytics appliance part of IBM PureSystemsSpaceTime is a spatio-temporal DBMS with a focus on performance.
Primary database modelDocument store
Relational DBMS
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSSpatial DBMS
Secondary database modelsDocument storeRelational 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
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Websitewww.databricks.comwww.intersystems.com/­products/­cachewww.ibm.com/­products/­netezzawww.mireo.com/­spacetime
Technical documentationdocs.databricks.comdocs.intersystems.com
DeveloperDatabricksInterSystemsIBMMireo
Initial release2013199720002020
Current release2018.1.4, May 2020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux infoincluded in applianceLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)depending on used data modelyesyes
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.yesyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesyesA subset of ANSI SQL is implemented
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesPython
R
Scala
C#
C++
Java
C
C++
Fortran
Java
Lua
Perl
Python
R
C#
C++
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyesno
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingFixed-grid hypercubes
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationSource-replica replicationReal-time block device replication (DRBD)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
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 dataACIDACIDACIDno
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 rolesUsers with fine-grained authorization conceptyes
More information provided by the system vendor
DatabricksInterSystems CachéNetezza infoAlso called PureData System for Analytics by IBMSpaceTime
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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