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DBMS > Databricks vs. IBM Db2 Event Store vs. Riak TS vs. Spark SQL

System Properties Comparison Databricks vs. IBM Db2 Event Store vs. Riak TS vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRiak TS  Xexclude from comparisonSpark SQL  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.Distributed Event Store optimized for Internet of Things use casesRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Event Store
Time Series DBMS
Time Series DBMSRelational 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
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comwww.ibm.com/­products/­db2-event-storespark.apache.org/­sql
Technical documentationdocs.databricks.comwww.ibm.com/­docs/­en/­db2-event-storewww.tiot.jp/­riak-docs/­riak/­ts/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksIBMOpen Source, formerly Basho TechnologiesApache Software Foundation
Initial release2013201720152014
Current release2.03.0.0, September 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++ErlangScala
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Linux
OS X
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.yesnonono
Secondary indexesyesnorestrictedno
SQL infoSupport of SQLwith Databricks SQLyes infothrough the embedded Spark runtimeyes, limitedSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesPython
R
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
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
Java
Python
R
Scala
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 nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive-active shard replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnono
More information provided by the system vendor
DatabricksIBM Db2 Event StoreRiak TSSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksIBM Db2 Event StoreRiak TSSpark SQL
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