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DBMS > Apache Impala vs. Apache Phoenix vs. Google Cloud Spanner vs. Hive

System Properties Comparison Apache Impala vs. Apache Phoenix vs. Google Cloud Spanner vs. Hive

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHive  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA scale-out RDBMS with evolutionary schema built on Apache HBaseA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteimpala.apache.orgphoenix.apache.orgcloud.google.com/­spannerhive.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlphoenix.apache.orgcloud.google.com/­spanner/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationGoogleApache Software Foundation infoinitially developed by Facebook
Initial release2013201420172012
Current release4.1.0, June 20225.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemsLinuxLinux
Unix
Windows
hostedAll OS with a Java VM
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBCgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsnoyes 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 nodesselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication with 3 replicas for regional instances.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceHadoop integrationyes infousing Google Cloud Dataflowyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoStrict serializable isolationno
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess 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
Apache ImpalaApache PhoenixGoogle Cloud SpannerHive
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