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DBMS > Databricks vs. Netezza vs. Riak KV vs. Sadas Engine

System Properties Comparison Databricks vs. Netezza vs. Riak KV vs. Sadas Engine

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRiak KV  Xexclude from comparisonSadas Engine  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 PureSystemsDistributed, fault tolerant key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational 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
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websitewww.databricks.comwww.ibm.com/­products/­netezzawww.sadasengine.com
Technical documentationdocs.databricks.comwww.tiot.jp/­riak-docs/­riak/­kv/­latestwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperDatabricksIBMOpenSource, formerly Basho TechnologiesSADAS s.r.l.
Initial release2013200020092006
Current release3.2.0, December 20228.0
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editioncommercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++
Server operating systemshostedLinux infoincluded in applianceLinux
OS X
AIX
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesyesyesrestrictedyes
SQL infoSupport of SQLwith Databricks SQLyesnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
HTTP API
Native Erlang Interface
JDBC
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesErlangno
Triggersnoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.noyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlUsers with fine-grained authorization conceptyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksNetezza infoAlso called PureData System for Analytics by IBMRiak KVSadas Engine
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 IBMRiak KVSadas Engine
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