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DBMS > Apache Impala vs. Brytlyt vs. GridDB vs. PouchDB

System Properties Comparison Apache Impala vs. Brytlyt vs. GridDB vs. PouchDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonGridDB  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLScalable in-memory time series database optimized for IoT and Big DataJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSRelational DBMSTime Series DBMSDocument store
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Websiteimpala.apache.orgbrytlyt.iogriddb.netpouchdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.iodocs.griddb.netpouchdb.com/­guides
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytToshiba CorporationApache Software Foundation
Initial release2013201620132012
Current release4.1.0, June 20225.0, August 20235.1, August 20227.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++ and CUDAC++JavaScript
Server operating systemsLinuxLinux
OS X
Windows
Linuxserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesyes infovia views
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLnoView functions in JavaScript
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationMulti-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 MapReducenoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelno
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache ImpalaBrytlytGridDBPouchDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache ImpalaBrytlytGridDBPouchDB
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