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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBigObject  Xexclude from comparisonFeatureBase  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAnalytic DBMS for real-time computations and queriesReal-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 Data
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Websiteimpala.apache.orgbigobject.iowww.featurebase.comgriddb.net
Technical documentationimpala.apache.org/­impala-docs.htmldocs.bigobject.iodocs.featurebase.comdocs.griddb.net
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBigObject, Inc.Molecula and Pilosa Open Source ContributorsToshiba Corporation
Initial release2013201520172013
Current release4.1.0, June 20222022, May 20225.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community edition availablecommercialOpen 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++GoC++
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
macOS
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsSQL queriesSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
ODBC
fluentd
ODBC
RESTful HTTP API
gRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCJava
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceLuano
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyesSource-replica replication
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 jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
Durability infoSupport for making data persistentyesyesyes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users can be defined per database
More information provided by the system vendor
Apache ImpalaBigObjectFeatureBaseGridDB
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 ImpalaBigObjectFeatureBaseGridDB
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