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DBMS > Drizzle vs. FatDB vs. Google Cloud Bigtable vs. Sqrrl

System Properties Comparison Drizzle vs. FatDB vs. Google Cloud Bigtable vs. Sqrrl

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSqrrl  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.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines 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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Adaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSDocument store
Key-value store
Key-value store
Wide column store
Document store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitecloud.google.com/­bigtablesqrrl.com
Technical documentationcloud.google.com/­bigtable/­docs
DeveloperDrizzle project, originally started by Brian AkerFatCloudGoogleAmazon infooriginally Sqrrl Data, Inc.
Initial release2008201220152012
Current release7.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#Java
Server operating systemsFreeBSD
Linux
OS X
WindowshostedLinux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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.no
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsno infoVia inetgration in SQL Servernono
APIs and other access methodsJDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C++
Java
PHP
C#C#
C++
Go
Java
JavaScript (Node.js)
Python
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyes infovia applicationsnono
Triggersno infohooks for callbacks inside the server can be used.yes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
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)Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
DrizzleFatDBGoogle Cloud BigtableSqrrl
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