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DBMS > Databricks vs. Netezza vs. TimesTen

System Properties Comparison Databricks vs. Netezza vs. TimesTen

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonTimesTen  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.Data warehouse and analytics appliance part of IBM PureSystemsAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score83.29
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score8.15
Rank#46  Overall
#30  Relational DBMS
Score1.26
Rank#164  Overall
#76  Relational DBMS
Websitewww.databricks.comwww.ibm.com/­products/­netezzawww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.databricks.comdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperDatabricksIBMOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release201320001998
Current releaseRelease 22.1
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Server operating systemshostedLinux infoincluded in applianceIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
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
JDBC
ODBC
OLE DB
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesPython
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesPL/SQL
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
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 persistentyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksNetezza infoAlso called PureData System for Analytics by IBMTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksNetezza infoAlso called PureData System for Analytics by IBMTimesTen
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