DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. BaseX vs. Databricks vs. PouchDB

System Properties Comparison Apache Impala vs. BaseX vs. Databricks vs. PouchDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBaseX  Xexclude from comparisonDatabricks  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.The 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.JavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSNative XML DBMSDocument store
Relational DBMS
Document store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.84
Rank#135  Overall
#4  Native XML DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websiteimpala.apache.orgbasex.orgwww.databricks.compouchdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.basex.orgdocs.databricks.compouchdb.com/­guides
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBaseX GmbHDatabricksApache Software Foundation
Initial release2013200720132012
Current release4.1.0, June 202211.0, June 20247.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSD licensecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaScript
Server operating systemsLinuxLinux
OS X
Windows
hostedserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesno
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.noyesno
Secondary indexesyesyesyesyes infovia views
SQL infoSupport of SQLSQL-like DML and DDL statementsnowith Databricks SQLno
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functions and aggregatesView functions in JavaScript
Triggersnoyes infovia eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writerACIDno
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept on 4 levelsno
More information provided by the system vendor
Apache ImpalaBaseXDatabricksPouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaBaseXDatabricksPouchDB
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

show all

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

XML Injection Attacks: What to Know About XPath, XQuery, XXE & More
18 May 2022, Hashed Out by The SSL Store™

9 Skills You Need to Become a Data Engineer
2 November 2022, KDnuggets

Xml Databases Software Market Thriving at a Tremendous Growth – TIMC
16 June 2024, TIMC

provided by Google News

Databricks is Taking the Ultimate Risk of Building 'USB for AI' – AIM
15 June 2024, Analytics India Magazine

The Three Big Announcements by Databricks AI Team in June 2024
17 June 2024, MarkTechPost

Databricks launches LakeFlow to help its customers build their data pipelines
12 June 2024, TechCrunch

Databricks tells investors annualized revenue will reach $2.4 billion at midway point of year
13 June 2024, CNBC

Databricks open-sources Unity Catalog, challenging Snowflake on interoperability for data workloads
12 June 2024, VentureBeat

provided by Google News

Building an Offline First App with PouchDB — SitePoint
10 March 2014, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database — SitePoint
7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, ibm.com

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
7 March 2017, SitePoint

Offline-first web and mobile apps: Top frameworks and components
22 January 2019, TechBeacon

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here