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DBMS > Apache Impala vs. Linter vs. PouchDB vs. TimescaleDB vs. Yanza

System Properties Comparison Apache Impala vs. Linter vs. PouchDB vs. TimescaleDB vs. Yanza

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonLinter  Xexclude from comparisonPouchDB  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopRDBMS for high security requirementsJavaScript DBMS with an API inspired by CouchDBA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSDocument storeTime Series DBMSTime Series DBMS
Secondary database modelsDocument storeSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteimpala.apache.orglinter.rupouchdb.comwww.timescale.comyanza.com
Technical documentationimpala.apache.org/­impala-docs.htmlpouchdb.com/­guidesdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by Clouderarelex.ruApache Software FoundationTimescaleYanza
Initial release20131990201220172015
Current release4.1.0, June 20227.1.1, June 20192.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen SourceOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++JavaScriptC
Server operating systemsLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Windows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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.nononoyesno
Secondary indexesyesyesyes infovia viewsyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
HTTP REST infoonly for PouchDB Server
JavaScript API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
JavaScript.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoproprietary syntax with the possibility to convert from PL/SQLView functions in JavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersnoyesyesyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infowith a proxy-based framework, named couchdb-loungeyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Source-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardno

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More resources
Apache ImpalaLinterPouchDBTimescaleDBYanza
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