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DBMS > Apache Impala vs. FeatureBase vs. GridDB vs. Linter

System Properties Comparison Apache Impala vs. FeatureBase vs. GridDB vs. Linter

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFeatureBase  Xexclude from comparisonGridDB  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Scalable in-memory time series database optimized for IoT and Big DataRDBMS for high security requirements
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Websiteimpala.apache.orgwww.featurebase.comgriddb.netlinter.ru
Technical documentationimpala.apache.org/­impala-docs.htmldocs.featurebase.comdocs.griddb.net
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMolecula and Pilosa Open Source ContributorsToshiba Corporationrelex.ru
Initial release2013201720131990
Current release4.1.0, June 20222022, May 20225.1, August 2022
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 availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoC++C and C++
Server operating systemsLinuxLinux
macOS
LinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL queriesSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsJDBC
ODBC
gRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesAll languages supporting JDBC/ODBCJava
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyes
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 KerberosAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaFeatureBaseGridDBLinter
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaFeatureBaseGridDBLinter
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