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DBMS > Apache Impala vs. Databricks vs. PouchDB vs. Valentina Server vs. YottaDB

System Properties Comparison Apache Impala vs. Databricks vs. PouchDB vs. Valentina Server vs. YottaDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonPouchDB  Xexclude from comparisonValentina Server  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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 CouchDBObject-relational database and reports serverA fast and solid embedded Key-value store
Primary database modelRelational DBMSDocument store
Relational DBMS
Document storeRelational DBMSKey-value store
Secondary database modelsDocument storeRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score0.21
Rank#325  Overall
#144  Relational DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websiteimpala.apache.orgwww.databricks.compouchdb.comwww.valentina-db.netyottadb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.compouchdb.com/­guidesvalentina-db.com/­docs/­dokuwiki/­v5/­doku.phpyottadb.com/­resources/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksApache Software FoundationParadigma SoftwareYottaDB, LLC
Initial release20132013201219992001
Current release4.1.0, June 20227.1.1, June 20195.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen SourcecommercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScriptC
Server operating systemsLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Docker
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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.noyesnono
Secondary indexesyesyesyes infovia viewsyesno
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLnoyesby using the Octo plugin
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
ODBCPostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
JavaScript.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesView functions in JavaScriptyes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standardUsers and groups based on OS-security mechanisms
More information provided by the system vendor
Apache ImpalaDatabricksPouchDBValentina ServerYottaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksPouchDBValentina ServerYottaDB
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