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DBMS > Drizzle vs. FatDB vs. Google Cloud Datastore vs. SQream DB vs. TimescaleDB

System Properties Comparison Drizzle vs. FatDB vs. Google Cloud Datastore vs. SQream DB vs. TimescaleDB

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSQream DB  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.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platforma GPU-based, columnar RDBMS for big data analytics workloadsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument store
Key-value store
Document storeRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score0.62
Rank#234  Overall
#109  Relational DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitecloud.google.com/­datastoresqream.comwww.timescale.com
Technical documentationcloud.google.com/­datastore/­docsdocs.sqream.comdocs.timescale.com
DeveloperDrizzle project, originally started by Brian AkerFatCloudGoogleSQream TechnologiesTimescale
Initial release20082012200820172017
Current release7.2.4, September 20122022.1.6, December 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#C++, CUDA, Haskell, Java, ScalaC
Server operating systemsFreeBSD
Linux
OS X
WindowshostedLinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes, ANSI Standard SQL Typesnumerics, 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.noyes
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsno infoVia inetgration in SQL ServerSQL-like query language (GQL)yesyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.Net
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Java
PHP
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infovia applicationsusing Google App Engineuser defined functions in Pythonuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersno infohooks for callbacks inside the server can be used.yes infovia applicationsCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal and vertical partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replication using PaxosnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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.nono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
DrizzleFatDBGoogle Cloud DatastoreSQream DBTimescaleDB
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