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DBMS > Apache Impala vs. Badger vs. Brytlyt vs. GBase

System Properties Comparison Apache Impala vs. Badger vs. Brytlyt vs. GBase

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonBrytlyt  Xexclude from comparisonGBase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.14
Rank#328  Overall
#48  Key-value stores
Score0.27
Rank#292  Overall
#132  Relational DBMS
Score1.11
Rank#173  Overall
#78  Relational DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerbrytlyt.iowww.gbase.cn
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.brytlyt.io
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsBrytlytGeneral Data Technology Co., Ltd.
Initial release2013201720162004
Current release4.1.0, June 20225.0, August 2023GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialcommercial
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 CUDAC, Java, Python
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.yes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesStandard with numerous extensions
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
C API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGo.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C#
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functions infoin PL/pgSQLuser defined functions
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning (by range, list and hash) and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standardyes

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More resources
Apache ImpalaBadgerBrytlytGBase
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