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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonGBase  Xexclude from comparisonHeroic  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelRelational DBMSRelational 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
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Websiteimpala.apache.orgwww.esgyn.cnwww.gbase.cngithub.com/­spotify/­heroic
Technical documentationimpala.apache.org/­impala-docs.htmlspotify.github.io/­heroic
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynGeneral Data Technology Co., Ltd.Spotify
Initial release2013201520042014
Current release4.1.0, June 2022GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaC, Java, PythonJava
Server operating systemsLinuxLinuxLinux
Data schemeyesyesyesschema-free
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.nonoyesno
Secondary indexesyesyesyesyes infovia Elasticsearch
SQL infoSupport of SQLSQL-like DML and DDL statementsyesStandard with numerous extensionsno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
ADO.NET
C API
JDBC
ODBC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetC#
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresuser defined functionsno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyes

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More resources
Apache ImpalaEsgynDBGBaseHeroic
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