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DBMS > Databricks vs. Geode vs. MonetDB vs. PouchDB

System Properties Comparison Databricks vs. Geode vs. MonetDB vs. PouchDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeode  Xexclude from comparisonMonetDB  Xexclude from comparisonPouchDB  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 processesA relational database management system that stores data in columnsJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSDocument store
Secondary database modelsDocument store
Spatial 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
Score1.86
Rank#134  Overall
#24  Key-value stores
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitewww.databricks.comgeode.apache.orgwww.monetdb.orgpouchdb.com
Technical documentationdocs.databricks.comgeode.apache.org/­docswww.monetdb.org/­Documentationpouchdb.com/­guides
DeveloperDatabricksOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.MonetDB BVApache Software Foundation
Initial release2013200220042012
Current release1.1, February 2017Dec2023 (11.49), December 20237.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoMozilla Public License 2.0Open Source
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaScript
Server operating systemshostedAll OS with a Java VM infothe JDK (8 or later) is also requiredFreeBSD
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)
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.yesnono
Secondary indexesyesnoyesyes infovia views
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (OQL)yes infoSQL 2003 with some extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesPython
R
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyes, in SQL, C, RView functions in JavaScript
Triggersyes infoCache Event Listenersyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding via remote tablesSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationnone infoSource-replica replication available in experimental statusMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights per client and object definablefine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksGeodeMonetDBPouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGeodeMonetDBPouchDB
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