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DBMS > Apache Impala vs. Netezza vs. Spark SQL vs. Yaacomo

System Properties Comparison Apache Impala vs. Netezza vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  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 PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.ibm.com/­products/­netezzaspark.apache.org/­sqlyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMApache Software FoundationQ2WEB GmbH
Initial release2013200020142009
Current release4.1.0, June 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinuxLinux infoincluded in applianceLinux
OS X
Windows
Android
Linux
Windows
Data schemeyesyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
OLE DB
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesno
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard

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

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

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

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

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

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

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Cloudera: Impala's it for interactive SQL on Hadoop; everything else will move to Spark
11 April 2024, Yahoo Movies Canada

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

provided by Google News



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