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DBMS > Apache Impala vs. Atos Standard Common Repository vs. GigaSpaces vs. Netezza vs. Postgres-XL

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. GigaSpaces vs. Netezza vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGigaSpaces  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPostgres-XL  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 networksHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsData warehouse and analytics appliance part of IBM PureSystemsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS
Secondary database modelsDocument storeGraph DBMS
Search engine
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gigaspaces.comwww.ibm.com/­products/­netezzawww.postgres-xl.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.gigaspaces.com/­latest/­landing.htmlwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsGigaspaces TechnologiesIBM
Initial release20132016200020002014 infosince 2012, originally named StormDB
Current release4.1.0, June 2022170315.5, September 202010 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava, C++, .NetC
Server operating systemsLinuxLinuxLinux
macOS
Solaris
Windows
Linux infoincluded in applianceLinux
macOS
Data schemeyesSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyesyes
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.noyesno infoXML can be used for describing objects metadatayes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-99 for query and DML statementsyesyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
LDAPGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindings.Net
C++
Java
Python
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesyesuser defined functions
Triggersnoyesyes, event driven architecturenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoMap-Reduce pattern can be built with XAP task executorsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDACIDACID infoMVCC
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.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationRole-based access controlUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Apache ImpalaAtos Standard Common RepositoryGigaSpacesNetezza infoAlso called PureData System for Analytics by IBMPostgres-XL
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