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

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

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDrizzle  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.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed 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.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 DBMSRelational DBMSKey-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
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/­bigtablesqrrl.com
Technical documentationdocs.databend.comcloud.google.com/­bigtable/­docs
DeveloperDatabend LabsDrizzle project, originally started by Brian AkerGoogleAmazon infooriginally Sqrrl Data, Inc.
Initial release2021200820152012
Current release1.0.59, April 20237.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustC++Java
Server operating systemshosted
Linux
macOS
FreeBSD
Linux
OS X
hostedLinux
Data schemeyesyesschema-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.nono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsnono
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C
C++
Java
PHP
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 proceduresnononono
Triggersnono infohooks for callbacks inside the server can be used.nono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Internal 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 methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDAtomic 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 controlUsers with fine-grained authorization concept, user rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess 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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DatabendDrizzleGoogle Cloud BigtableSqrrl
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