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DBMS > Databricks vs. Faircom EDGE vs. PouchDB vs. Tkrzw

System Properties Comparison Databricks vs. Faircom EDGE vs. PouchDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonPouchDB  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.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsJavaScript DBMS with an API inspired by CouchDBA 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 store
Relational DBMS
Document storeKey-value 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
Score0.02
Rank#370  Overall
#55  Key-value stores
#157  Relational DBMS
Score2.18
Rank#114  Overall
#21  Document stores
Score0.00
Rank#385  Overall
#61  Key-value stores
Websitewww.databricks.comwww.faircom.com/­products/­faircom-edgepouchdb.comdbmx.net/­tkrzw
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlpouchdb.com/­guides
DeveloperDatabricksFairCom CorporationApache Software FoundationMikio Hirabayashi
Initial release2013197920122020
Current releaseV3, October 20207.1.1, June 20190.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen SourceOpen 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 languageANSI C, C++JavaScriptC++
Server operating systemshostedAndroid
Linux infoARM, x86
Raspbian
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)Flexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesnono
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.yesyesnono
Secondary indexesyesyesyes infovia views
SQL infoSupport of SQLwith Databricks SQLyes infoANSI SQL queriesnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesPython
R
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
JavaScriptC++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes info.Net, JavaScript, C/C++View functions in JavaScriptno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningSharding infowith a proxy-based framework, named couchdb-loungenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infousing specific database classes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.nono
More information provided by the system vendor
DatabricksFaircom EDGE infoformerly c-treeEDGEPouchDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFaircom EDGE infoformerly c-treeEDGEPouchDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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