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DBMS > Databricks vs. Firebase Realtime Database vs. HBase vs. Newts vs. PouchDB

System Properties Comparison Databricks vs. Firebase Realtime Database vs. HBase vs. Newts vs. PouchDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHBase  Xexclude from comparisonNewts  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.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Wide-column store based on Apache Hadoop and on concepts of BigTableTime Series DBMS based on CassandraJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument store
Relational DBMS
Document storeWide column storeTime Series DBMSDocument 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
Score14.29
Rank#39  Overall
#6  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Websitewww.databricks.comfirebase.google.com/­products/­realtime-databasehbase.apache.orgopennms.github.io/­newtspouchdb.com
Technical documentationdocs.databricks.comfirebase.google.com/­docs/­databasehbase.apache.org/­book.htmlgithub.com/­OpenNMS/­newts/­wikipouchdb.com/­guides
DeveloperDatabricksGoogle infoacquired by Google 2014Apache Software Foundation infoApache top-level project, originally developed by PowersetOpenNMS GroupApache Software Foundation
Initial release20132012200820142012
Current release2.3.4, January 20217.1.1, June 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaScript
Server operating systemshostedhostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleschema-freeschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesno
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.yesnononono
Secondary indexesyesyesnonoyes infovia views
SQL infoSupport of SQLwith Databricks SQLnononono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
HTTP REST
Java API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesPython
R
Scala
Java
JavaScript
Objective-C
C
C#
C++
Groovy
Java
PHP
Python
Scala
JavaJavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregateslimited functionality with using 'rules'yes infoCoprocessors in JavanoView functions in JavaScript
TriggersCallbacks are triggered when data changesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.noyesnoyes
User concepts infoAccess controlyes, based on authentication and database rulesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono
More information provided by the system vendor
DatabricksFirebase Realtime DatabaseHBaseNewtsPouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFirebase Realtime DatabaseHBaseNewtsPouchDB
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