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DBMS > Amazon Redshift vs. BoltDB vs. Drizzle vs. Google BigQuery vs. TimescaleDB

System Properties Comparison Amazon Redshift vs. BoltDB vs. Drizzle vs. Google BigQuery vs. TimescaleDB

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonBoltDB  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionLarge scale data warehouse service for use with business intelligence toolsAn embedded key-value store for Go.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Large scale data warehouse service with append-only tablesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score0.74
Rank#220  Overall
#31  Key-value stores
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteaws.amazon.com/­redshiftgithub.com/­boltdb/­boltcloud.google.com/­bigquerywww.timescale.com
Technical documentationdocs.aws.amazon.com/­redshiftcloud.google.com/­bigquery/­docsdocs.timescale.com
DeveloperAmazon (based on PostgreSQL)Drizzle project, originally started by Brian AkerGoogleTimescale
Initial release20122013200820102017
Current release7.2.4, September 20122.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCGoC++C
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesrestrictednoyesnoyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardnoyes infowith proprietary extensionsyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
JDBCRESTful HTTP/JSON APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCGoC
C++
Java
PHP
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin Pythonnonouser defined functions infoin JavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonono infohooks for callbacks inside the server can be used.noyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDno infoSince BigQuery is designed for querying dataACID
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.yesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Amazon RedshiftBoltDBDrizzleGoogle BigQueryTimescaleDB
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