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DBMS > Amazon Redshift vs. Hypertable vs. Impala

System Properties Comparison Amazon Redshift vs. Hypertable vs. Impala

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonHypertable  Xexclude from comparisonImpala  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionLarge scale data warehouse service for use with business intelligence toolsAn open source BigTable implementation based on distributed file systems such as HadoopAnalytic DBMS for Hadoop
Primary database modelRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score22.37
Rank#30  Overall
#17  Relational DBMS
Score15.52
Rank#36  Overall
#22  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.html
Technical documentationdocs.aws.amazon.com/­redshiftdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.html
DeveloperAmazon (based on PostgreSQL)Hypertable Inc.Cloudera
Initial release201220092013
Current release0.9.8.11, March 20163.3.0, August 2019
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++C++
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesrestrictedrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
C++ API
Thrift
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC
Server-side scripts infoStored proceduresuser defined functions infoin Pythonnoyes infouser defined functions and integration of map-reduce
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor on file system levelselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles infobased on Apache Sentry and Kerberos

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More resources
Amazon RedshiftHypertableImpala
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