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DBMS > Apache Impala vs. GridGain vs. Netezza vs. SpaceTime vs. Yaacomo

System Properties Comparison Apache Impala vs. GridGain vs. Netezza vs. SpaceTime vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridGain  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpaceTime  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopGridGain is an in-memory computing platform, built on Apache IgniteData warehouse and analytics appliance part of IBM PureSystemsSpaceTime is a spatio-temporal DBMS with a focus on performance.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSSpatial DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Websiteimpala.apache.orgwww.gridgain.comwww.ibm.com/­products/­netezzawww.mireo.com/­spacetimeyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.gridgain.com/­docs/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGridGain Systems, Inc.IBMMireoQ2WEB GmbH
Initial release20132007200020202009
Current release4.1.0, June 2022GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialcommercial
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++Java, C++, .NetC++
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Linux infoincluded in applianceLinuxAndroid
Linux
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 statementsANSI-99 for query and DML statements, subset of DDLyesA subset of ANSI SQL is implementedyes
APIs and other access methodsJDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
OLE DB
RESTful HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C#
C++
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)yesno
Triggersnoyes (cache interceptors and events)nonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingFixed-grid hypercubeshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)Source-replica replicationReal-time block device replication (DRBD)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)yesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
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.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosSecurity Hooks for custom implementationsUsers with fine-grained authorization conceptyesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaGridGainNetezza infoAlso called PureData System for Analytics by IBMSpaceTimeYaacomo
Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
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AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

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