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DBMS > Databricks vs. Datomic vs. Geode vs. PouchDB

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonGeode  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.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score1.51
Rank#147  Overall
#25  Key-value stores
Score2.18
Rank#114  Overall
#21  Document stores
Websitewww.databricks.comwww.datomic.comgeode.apache.orgpouchdb.com
Technical documentationdocs.databricks.comdocs.datomic.comgeode.apache.org/­docspouchdb.com/­guides
DeveloperDatabricksCognitectOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software Foundation
Initial release2013201220022012
Current release1.0.7180, July 20241.1, February 20177.1.1, June 2019
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaJavaScript
Server operating systemshostedAll OS with a Java VMAll OS with a Java VM infothe JDK (8 or later) is also requiredserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-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 indexesyesyesnoyes infovia views
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (OQL)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJava Client API
Memcached protocol
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesPython
R
Scala
Clojure
Java
.Net
All JVM based languages
C++
Groovy
Java
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoTransaction Functionsuser defined functionsView functions in JavaScript
TriggersBy using transaction functionsyes infoCache Event Listenersyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersMulti-source replicationMulti-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 ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes, on a single nodeno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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.noyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlnoAccess rights per client and object definableno
More information provided by the system vendor
DatabricksDatomicGeodePouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDatomicGeodePouchDB
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