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DBMS > Apache Impala vs. Kdb vs. Transwarp Hippo vs. Yaacomo

System Properties Comparison Apache Impala vs. Kdb vs. Transwarp Hippo vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKdb  Xexclude from comparisonTranswarp Hippo  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 DBMSCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasetsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSTime Series DBMS
Vector DBMS
Vector 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
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.05
Rank#386  Overall
#14  Vector DBMS
Websiteimpala.apache.orgkx.comwww.transwarp.cn/­en/­subproduct/­hippoyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlcode.kx.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKx Systems, a division of First Derivatives plcQ2WEB GmbH
Initial release20132000 infokdb was released 2000, kdb+ in 200320232009
Current release4.1.0, June 20223.6, May 20181.0, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree 32-bit versioncommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++qC++
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Linux
macOS
Android
Linux
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes
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'noyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (q)noyes
APIs and other access methodsJDBC
ODBC
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
RESTful HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C++
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsno
Triggersnoyes infowith viewsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno infosimilar paradigm used for internal processingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsRole based access control and fine grained access rightsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaKdbTranswarp HippoYaacomo
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

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More resources
Apache ImpalaKdbTranswarp HippoYaacomo
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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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

provided by Google News

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18 May 2023, AWS Blog

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

Q/Kdb+ on AWS Lambda: Serverless Time-Series Analytics at Scale | Amazon Web Services
12 May 2020, AWS Blog

provided by Google News



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