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DBMS > Apache Impala vs. Google Cloud Spanner vs. Kdb vs. Netezza vs. Yaacomo

System Properties Comparison Apache Impala vs. Google Cloud Spanner vs. Kdb vs. Netezza vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKdb  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 HadoopA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.High performance Time Series DBMSData warehouse and analytics appliance part of IBM PureSystemsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­spannerkx.comwww.ibm.com/­products/­netezzayaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docscode.kx.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleKx Systems, a division of First Derivatives plcIBMQ2WEB GmbH
Initial release201320172000 infokdb was released 2000, kdb+ in 200320002009
Current release4.1.0, June 20223.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree 32-bit versioncommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++q
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Linux 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.nonoyesno
Secondary indexesyesyesyes infotable attribute 'grouped'yesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoQuery statements complying to ANSI 2011SQL-like query language (q)yesyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functionsyes
Triggersnonoyes infowith viewsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication with 3 replicas for regional instances.Source-replica replicationSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowno infosimilar paradigm used for internal processingyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationnoACIDACID
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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaGoogle Cloud SpannerKdbNetezza 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...
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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
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More resources
Apache ImpalaGoogle Cloud SpannerKdbNetezza infoAlso called PureData System for Analytics by IBMYaacomo
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