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DBMS > Databricks vs. Hypertable vs. Netezza

System Properties Comparison Databricks vs. Hypertable vs. Netezza

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHypertable  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and 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.An open source BigTable implementation based on distributed file systems such as HadoopData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument store
Relational DBMS
Wide column storeRelational 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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitewww.databricks.comwww.ibm.com/­products/­netezza
Technical documentationdocs.databricks.com
DeveloperDatabricksHypertable Inc.IBM
Initial release201320092000
Current release0.9.8.11, March 2016
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux infoincluded in appliance
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyes
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.yes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLwith Databricks SQLnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
C++ API
Thrift
JDBC
ODBC
OLE DB
Supported programming languagesPython
R
Scala
C++
Java
Perl
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.no
User concepts infoAccess controlnoUsers with fine-grained authorization concept
More information provided by the system vendor
DatabricksHypertableNetezza 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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