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DBMS > Amazon Redshift vs. Apache Impala vs. Google Cloud Bigtable vs. Hive

System Properties Comparison Amazon Redshift vs. Apache Impala vs. Google Cloud Bigtable vs. Hive

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.03
Rank#34  Overall
#21  Relational DBMS
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Websiteaws.amazon.com/­redshiftimpala.apache.orgcloud.google.com/­bigtablehive.apache.org
Technical documentationdocs.aws.amazon.com/­redshiftimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleApache Software Foundation infoinitially developed by Facebook
Initial release2012201320152012
Current release4.1.0, June 20223.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++Java
Server operating systemshostedLinuxhostedAll OS with a Java VM
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonono
Secondary indexesrestrictedyesnoyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes infouser defined functions and integration of map-reducenoyes infouser defined functions and integration of map-reduce
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsno
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles

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More resources
Amazon RedshiftApache ImpalaGoogle Cloud BigtableHive
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