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DBMS > Google BigQuery vs. Kinetica vs. LeanXcale

System Properties Comparison Google BigQuery vs. Kinetica vs. LeanXcale

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonKinetica  Xexclude from comparisonLeanXcale  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesFully vectorized database across both GPUs and CPUsA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score63.63
Rank#19  Overall
#13  Relational DBMS
Score0.80
Rank#226  Overall
#104  Relational DBMS
Score0.27
Rank#315  Overall
#46  Key-value stores
#140  Relational DBMS
Websitecloud.google.com/­bigquerywww.kinetica.comwww.leanxcale.com
Technical documentationcloud.google.com/­bigquery/­docsdocs.kinetica.com
DeveloperGoogleKineticaLeanXcale
Initial release201020122015
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++
Server operating systemshostedLinux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infothrough Apache Derby
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
Java
Scala
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptuser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users and roles on table level

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More resources
Google BigQueryKineticaLeanXcale
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