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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Bangdb vs. Greenplum vs. Hive

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Bangdb vs. Greenplum vs. Hive

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonBangdb  Xexclude from comparisonGreenplum  Xexclude from comparisonHive  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksConverged and high performance database for device data, events, time series, document and graphAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Graph DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorybangdb.comgreenplum.orghive.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.bangdb.comdocs.greenplum.orgcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsSachin Sinha, BangDBPivotal Software Inc.Apache Software Foundation infoinitially developed by Facebook
Initial release20132016201220052012
Current release4.1.0, June 20221703BangDB 2.0, October 20217.0.0, September 20233.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBSD 3Open Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC, C++Java
Server operating systemsLinuxLinuxLinuxLinuxAll OS with a Java VM
Data schemeyesSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptionalyes: string, long, double, int, geospatial, stream, eventsyesyes
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.noyesnoyes infosince Version 4.2
Secondary indexesyesyesyes infosecondary, composite, nested, reverse, geospatialyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL like support with command line toolyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
LDAPProprietary protocol
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsC
C#
C++
Java
Python
C
Java
Perl
Python
R
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyesyes infouser defined functions and integration of map-reduce
Triggersnoyesyes, Notifications (with Streaming only)yesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationTunable consistency, set CAP knob accordinglyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, run db with in-memory only modeno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationyes (enterprise version only)fine grained access rights according to SQL-standardAccess rights for users, groups and roles

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More resources
Apache ImpalaAtos Standard Common RepositoryBangdbGreenplumHive
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