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DBMS > Coveo vs. Google BigQuery vs. Netezza vs. Spark SQL vs. Transbase

System Properties Comparison Coveo vs. Google BigQuery vs. Netezza vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentLarge scale data warehouse service with append-only tablesData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelSearch engineRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.11
Rank#118  Overall
#11  Search engines
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.coveo.comcloud.google.com/­bigquerywww.ibm.com/­products/­netezzaspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.coveo.comcloud.google.com/­bigquery/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCoveoGoogleIBMApache Software FoundationTransaction Software GmbH
Initial release20122010200020141987
Current release3.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC and C++
Server operating systemshostedhostedLinux infoincluded in applianceLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesyesyesyes
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.nononono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLnoyesyesSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIJDBC
ODBC
OLE DB
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
Java
JavaScript
Python
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptyesnoyes
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodesyesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesno infoSince BigQuery is designed for querying dataACIDnoyes
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.nonono
User concepts infoAccess controlgranular access controls, API key management, content filtersAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Users with fine-grained authorization conceptnofine grained access rights according to SQL-standard

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More resources
CoveoGoogle BigQueryNetezza infoAlso called PureData System for Analytics by IBMSpark SQLTransbase
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