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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonEJDB  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMSRelational DBMSDocument storeTime Series DBMS
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
Score0.27
Rank#297  Overall
#44  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websiteimpala.apache.orgbrytlyt.iogithub.com/­Softmotions/­ejdbgriddb.net
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.iogithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.griddb.net
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytSoftmotionsToshiba Corporation
Initial release2013201620122013
Current release4.1.0, June 20225.0, August 20235.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPLv2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
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 CUDACC++
Server operating systemsLinuxLinux
OS X
Windows
server-lessLinux
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, bool, date, object_idyes infonumerical, string, blob, geometry, boolean, timestamp
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.no
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
in-process shared libraryJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLnono
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyesno infotypically not needed, however similar functionality with collection joins possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/Write Lockingyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardnoAccess rights for users can be defined per database
More information provided by the system vendor
Apache ImpalaBrytlytEJDBGridDB
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 ImpalaBrytlytEJDBGridDB
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