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DBMS > Databricks vs. Geode vs. Spark SQL vs. Tkrzw

System Properties Comparison Databricks vs. Geode vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeode  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesSpark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comgeode.apache.orgspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationdocs.databricks.comgeode.apache.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software FoundationMikio Hirabayashi
Initial release2013200220142020
Current release1.1, February 20173.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++
Server operating systemshostedAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesnono
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (OQL)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnono
Triggersyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeno
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.noyesnoyes infousing specific database classes
User concepts infoAccess controlAccess rights per client and object definablenono
More information provided by the system vendor
DatabricksGeodeSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGeodeSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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