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DBMS > Apache Impala vs. Databend vs. EsgynDB vs. GBase

System Properties Comparison Apache Impala vs. Databend vs. EsgynDB vs. GBase

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabend  Xexclude from comparisonEsgynDB  Xexclude from comparisonGBase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational 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
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Websiteimpala.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
www.esgyn.cnwww.gbase.cn
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databend.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabend LabsEsgynGeneral Data Technology Co., Ltd.
Initial release2013202120152004
Current release4.1.0, June 20221.0.59, April 2023GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 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++RustC++, JavaC, Java, Python
Server operating systemsLinuxhosted
Linux
macOS
LinuxLinux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesStandard with numerous extensions
APIs and other access methodsJDBC
ODBC
CLI Client
JDBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
C API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
Rust
All languages supporting JDBC/ODBC/ADO.NetC#
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava Stored Proceduresuser defined functions
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardinghorizontal partitioning (by range, list and hash) and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication between multi datacentersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACID
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 KerberosUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardyes

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More resources
Apache ImpalaDatabendEsgynDBGBase
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