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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonBrytlyt  Xexclude from comparisonDatabend  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 PostgreSQLAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity
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
Score0.28
Rank#287  Overall
#131  Relational DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerbrytlyt.iogithub.com/­datafuselabs/­databend
www.databend.com
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.brytlyt.iodocs.databend.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsBrytlytDatabend Labs
Initial release2013201720162021
Current release4.1.0, June 20225.0, August 20231.0.59, April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC, C++ and CUDARust
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
hosted
Linux
macOS
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.no
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
CLI Client
JDBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCGo.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functions infoin PL/pgSQLno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDyes
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-standardUsers with fine-grained authorization concept, user roles

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More resources
Apache ImpalaBadgerBrytlytDatabend
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