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DBMS > Databend vs. Google Cloud Bigtable

System Properties Comparison Databend vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityGoogle'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 DBMSKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­bigtable
Technical documentationdocs.databend.comcloud.google.com/­bigtable/­docs
DeveloperDatabend LabsGoogle
Initial release20212015
Current release1.0.59, April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRust
Server operating systemshosted
Linux
macOS
hosted
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesno
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
SQL infoSupport of SQLyesno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
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 integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic single-row operations
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.no
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
DatabendGoogle Cloud Bigtable
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