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DBMS > Google BigQuery vs. ReductStore vs. Vertica

System Properties Comparison Google BigQuery vs. ReductStore vs. Vertica

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonReductStore  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score50.58
Rank#19  Overall
#13  Relational DBMS
Score0.01
Rank#379  Overall
#39  Time Series DBMS
Score9.38
Rank#42  Overall
#26  Relational DBMS
Websitecloud.google.com/­bigquerygithub.com/­reductstore
www.reduct.store
www.vertica.com
Technical documentationcloud.google.com/­bigquery/­docswww.reduct.store/­docsvertica.com/­documentation
DeveloperGoogleReductStore LLCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201020232005
Current release1.9, March 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoBusiness Source License 1.1commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, RustC++
Server operating systemshostedDocker
Linux
macOS
Windows
Linux
Data schemeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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 indexesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP/JSON APIHTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Google BigQueryReductStoreVertica infoOpenText™ Vertica™
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