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DBMS > Apache Impala vs. GBase vs. Google Cloud Datastore vs. HBase vs. Hive

System Properties Comparison Apache Impala vs. GBase vs. Google Cloud Datastore vs. HBase vs. Hive

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSRelational DBMSDocument storeWide column storeRelational 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
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websiteimpala.apache.orgwww.gbase.cncloud.google.com/­datastorehbase.apache.orghive.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docshbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGeneral Data Technology Co., Ltd.GoogleApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by Facebook
Initial release20132004200820082012
Current release4.1.0, June 2022GBase 8a, GBase 8s, GBase 8c2.3.4, January 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, Java, PythonJavaJava
Server operating systemsLinuxLinuxhostedLinux
Unix
Windows infousing Cygwin
All OS with a Java VM
Data schemeyesyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesyes, details hereoptions to bring your own types, AVROyes
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.noyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsStandard with numerous extensionsSQL-like query language (GQL)noSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
ADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsusing Google App Engineyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduce
TriggersnoyesCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication using PaxosMulti-source replication
Source-replica replication
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles

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More resources
Apache ImpalaGBaseGoogle Cloud DatastoreHBaseHive
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