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DBMS > EsgynDB vs. Impala

System Properties Comparison EsgynDB vs. Impala

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Our visitors often compare EsgynDB and Impala with Elasticsearch, Trafodion and Hive.

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonImpala  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAnalytic DBMS for Hadoop
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.18
Rank#261  Overall
#124  Relational DBMS
Score15.07
Rank#37  Overall
#23  Relational DBMS
Websiteesgyn.comwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.html
Technical documentationesgyn.com/­developerswww.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.html
DeveloperEsgynCloudera
Initial release20152013
Current release3.2.0, March 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++
Server operating systemsLinuxLinux
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.nono
Secondary indexesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetAll languages supporting JDBC/ODBC
Server-side scripts infoStored proceduresJava Stored Proceduresyes infouser defined functions and integration of map-reduce
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication between multi datacentersselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberos
More information provided by the system vendor
EsgynDBImpala
Specific characteristicsCapabilities for Operational/Transactional Workloads Deep Integration with HBase...
» more
Competitive advantagesEsgynDB is ideally suited to supporting Hybrid Transactional and Analytical Processing...
» more
Typical application scenariosIdeally suited to scenarios where high speed continuous data ingestion is required...
» more
Key customersEsgynDB's customers are worldwide, with several in the Global Fortune 500, including...
» more
Licensing and pricing modelsEsgynDB Enterprise Edition is the commercially supported version of Apache Trafodion...
» more

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More resources
EsgynDBImpala
Recent citations in the news

Esgyn Strato: Esgyn announces a Hybrid / Multi Cloud Big Data Platform Service to run and optimize your business
30 November 2018, Markets Insider

Mphasis partners with Esgyn Corporation to provide specialized solutions to clients looking to harness big data
28 May 2019, Moneycontrol

The Apache Software Foundation Announces Apache® Trafodion™ as a Top-Level Project
10 January 2018, GlobeNewswire

Mphasis partners with Esgyn Corporation to optimize Open-Source frameworks and expand industry footprint
24 May 2019, PRNewswire

provided by Google News

Cloudera's a data warehouse player now
28 August 2018, ZDNet

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10 November 2014, InformationWeek

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Cloudera says Impala is faster than Hive, which isn't saying much
13 January 2014, GigaOM

Cloudera: Impala's it for interactive SQL on Hadoop; everything else will move to Spark
3 July 2014, GigaOM

provided by Google News

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