DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

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

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

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDrizzle  Xexclude from comparisonEXASOL  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.High-performance, in-memory, MPP database specifically designed for in-memory analytics.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
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.exasol.comcloud.google.com/­bigtable
Technical documentationdocs.databend.comwww.exasol.com/­resourcescloud.google.com/­bigtable/­docs
DeveloperDatabend LabsDrizzle project, originally started by Brian AkerExasolGoogle
Initial release2021200820002015
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 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
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.nonono
Secondary indexesnoyesyesno
SQL infoSupport of SQLyesyes infowith proprietary extensionsyesno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC.Net
JDBC
ODBC
WebSocket
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
Java
Lua
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersnono infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
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 zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoHadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 datayesACIDACIDAtomic 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.yesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
DatabendDrizzleEXASOLGoogle Cloud Bigtable
DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Recent citations in the news

Data Bending: Creating Unique Digital Visual Effects
23 April 2020, RedShark News

Rust and the OS, the Web, Database and Other Languages
21 November 2022, The New Stack

£1.1 Million in AddisonMckee Tube Bending Technologies Provides Dinex with Outstanding OEM Credentials
24 May 2007, news.thomasnet.com

provided by Google News

It's Back to the Database Future for Exasol CEO Tewes
26 October 2023, Datanami

Mathias Golombek, Chief Technology Officer of Exasol – Interview Series
21 May 2024, Unite.AI

Exasol Finds AI Underinvestment Leads to Business Failure, But Data Challenges Stall Rapid Adoption
14 May 2024, insideBIGDATA

Exasol gets jolt of AI with Espresso suite of capabilities
26 February 2024, TechTarget

Exasol Unveils New Suite of AI Tools to Turbocharge Enterprise Data Analytics
21 February 2024, Business Wire

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News



Share this page

Featured Products

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here