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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpaceTime  Xexclude from comparisonVitess  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopData warehouse and analytics appliance part of IBM PureSystemsSpaceTime is a spatio-temporal DBMS with a focus on performance.Scalable, distributed, cloud-native DBMS, extending MySQLOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSSpatial DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteimpala.apache.orgwww.ibm.com/­products/­netezzawww.mireo.com/­spacetimevitess.ioyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlvitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMMireoThe Linux Foundation, PlanetScaleQ2WEB GmbH
Initial release20132000202020132009
Current release4.1.0, June 202215.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache Version 2.0, commercial licenses availablecommercial
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++C++Go
Server operating systemsLinuxLinux infoincluded in applianceLinuxDocker
Linux
macOS
Android
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.nonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesA subset of ANSI SQL is implementedyes infowith proprietary extensionsyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
OLE DB
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Fortran
Java
Lua
Perl
Python
R
C#
C++
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoyes infoproprietary syntax
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingFixed-grid hypercubesShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationReal-time block device replication (DRBD)Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization conceptyesUsers with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaNetezza infoAlso called PureData System for Analytics by IBMSpaceTimeVitessYaacomo
Recent citations in the news

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

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

Netezza Performance Server
12 August 2020, ibm.com

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News



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