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DBMS > Databricks vs. Ingres vs. Riak KV vs. Splice Machine

System Properties Comparison Databricks vs. Ingres vs. Riak KV vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonIngres  Xexclude from comparisonRiak KV  Xexclude from comparisonSplice Machine  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.Well established RDBMSDistributed, fault tolerant key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
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
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score3.63
Rank#79  Overall
#43  Relational DBMS
Score3.84
Rank#76  Overall
#9  Key-value stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitewww.databricks.comwww.actian.com/­databases/­ingressplicemachine.com
Technical documentationdocs.databricks.comdocs.actian.com/­ingreswww.tiot.jp/­riak-docs/­riak/­kv/­latestsplicemachine.com/­how-it-works
DeveloperDatabricksActian CorporationOpenSource, formerly Basho TechnologiesSplice Machine
Initial release20131974 infooriginally developed at University Berkely in early 1970s20092014
Current release12.0, July 20243.2.0, December 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCErlangJava
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Linux
OS X
Solaris
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.yesno infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesrestrictedyes
SQL infoSupport of SQLwith Databricks SQLyesnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
Supported programming languagesPython
R
Scala
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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesErlangyes infoJava
Triggersyesyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infono "single point of failure"Shared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesIngres Replicatorselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes, multi-version concurrency control (MVCC)
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksIngresRiak KVSplice Machine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksIngresRiak KVSplice Machine
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