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DBMS > Databend vs. Drizzle vs. FileMaker vs. Google Cloud Bigtable

System Properties Comparison Databend vs. Drizzle vs. FileMaker vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDrizzle  Xexclude from comparisonFileMaker  Xexclude from comparisonGoogle Cloud Bigtable  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.
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.FileMaker is a cross-platform RDBMS that includes a GUI frontend.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score45.20
Rank#20  Overall
#14  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.claris.com/­filemakercloud.google.com/­bigtable
Technical documentationdocs.databend.comwww.claris.com/­resources/­documentationcloud.google.com/­bigtable/­docs
DeveloperDatabend LabsDrizzle project, originally started by Brian AkerClaris infoa subsidiary of AppleGoogle
Initial release2021200819832015
Current release1.0.59, April 20237.2.4, September 201219.4.1, November 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++
Server operating systemshosted
Linux
macOS
FreeBSD
Linux
OS X
iOS infoclient part only
Linux
OS X
Windows
hosted
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 infoA http query request can return the data in XML formatno
Secondary indexesnoyesyesno
SQL infoSupport of SQLyesyes infowith proprietary extensionsyes infovia pluginsno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBCFilemaker WebDirect
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C
C++
Java
PHP
PHPC#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyesno
Triggersnono infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Source-replica replication, warm standby infosince Version 14Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnoAtomic single-row operations
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 controlUsers with fine-grained authorization concept, user rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPsimple rights management via user accounts and connection to external directory servicesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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DatabendDrizzleFileMakerGoogle Cloud Bigtable
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