DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. Kdb vs. Kinetica vs. Netezza vs. Yaacomo

System Properties Comparison Apache Impala vs. Kdb vs. Kinetica vs. Netezza vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKdb  Xexclude from comparisonKinetica  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopHigh performance Time Series DBMSFully vectorized database across both GPUs and CPUsData warehouse and analytics appliance part of IBM PureSystemsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSTime Series DBMS
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websiteimpala.apache.orgkx.comwww.kinetica.comwww.ibm.com/­products/­netezzayaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlcode.kx.comdocs.kinetica.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKx Systems, a division of First Derivatives plcKineticaIBMQ2WEB GmbH
Initial release20132000 infokdb was released 2000, kdb+ in 2003201220002009
Current release4.1.0, June 20223.6, May 20187.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree 32-bit versioncommercialcommercialcommercial
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++qC, C++
Server operating systemsLinuxLinux
OS X
Solaris
Windows
LinuxLinux infoincluded in applianceAndroid
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 indexesyesyes infotable attribute 'grouped'yesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (q)SQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsuser defined functionsyes
Triggersnoyes infowith viewsyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno infosimilar paradigm used for internal processingnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
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.noyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsAccess rights for users and roles on table levelUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaKdbKineticaNetezza infoAlso called PureData System for Analytics by IBMYaacomo
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaKdbKineticaNetezza infoAlso called PureData System for Analytics by IBMYaacomo
Recent citations in the news

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

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

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, 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

Turbocharging the Engine: KX Unleashes AI-First Transformation with kdb+
28 February 2024, Business Wire

McLaren Applied and KX partner to enhance ATLAS software analytics capabilities
9 August 2023, Professional Motorsport World

Introducing Amazon FinSpace with Managed kdb Insights, a fully managed analytics engine, commonly used by capital ...
18 May 2023, AWS Blog

KX ANNOUNCES KDB INSIGHTS AS FULLY MANAGED SERVICE ON AMAZON FINSPACE
18 May 2023, PR Newswire

KX Brings the Power and Performance of kdb+ to Python Developers with PyKX
7 June 2023, Datanami

provided by Google News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica Delivers Real-Time Vector Similarity Search
20 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
22 March 2024, Geospatial World

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

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

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

Netezza Performance Server
12 August 2020, IBM

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here