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DBMS > Apache Impala vs. GBase vs. ReductStore

System Properties Comparison Apache Impala vs. GBase vs. ReductStore

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGBase  Xexclude from comparisonReductStore  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websiteimpala.apache.orgwww.gbase.cngithub.com/­reductstore
www.reduct.store
Technical documentationimpala.apache.org/­impala-docs.htmlwww.reduct.store/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGeneral Data Technology Co., Ltd.ReductStore LLC
Initial release201320042023
Current release4.1.0, June 2022GBase 8a, GBase 8s, GBase 8c1.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, Java, PythonC++, Rust
Server operating systemsLinuxLinuxDocker
Linux
macOS
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsStandard with numerous extensions
APIs and other access methodsJDBC
ODBC
ADO.NET
C API
JDBC
ODBC
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes

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More resources
Apache ImpalaGBaseReductStore
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