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DBMS > CrateDB vs. Dragonfly vs. Google Cloud Bigtable

System Properties Comparison CrateDB vs. Dragonfly vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonDragonfly  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionDistributed Database based on LuceneA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceGoogle'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 modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeKey-value store
Wide column store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitecratedb.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­bigtable
Technical documentationcratedb.com/­docswww.dragonflydb.io/­docscloud.google.com/­bigtable/­docs
DeveloperCrateDragonflyDB team and community contributorsGoogle
Initial release201320232015
Current release1.0, March 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoBSL 1.1commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)scheme-freeschema-free
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysno
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 indexesyesnono
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynono
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)Luano
Triggersnopublish/subscribe channels provide some trigger functionalityno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyAtomic execution of command blocks and scriptsAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlrights management via user accountsPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
CrateDBDragonflyGoogle Cloud Bigtable
Recent citations in the news

AWS Marketplace: CrateDB Cloud Comments
12 June 2024, AWS Blog

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT
25 March 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions
16 May 2017, businesswire.com

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21 March 2023, SiliconANGLE News

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20 March 2023, Phoronix

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29 March 2023, Phoronix

SFU Computing Science researchers receive 2022 ACM SIGMOD Research Highlight Award.
24 February 2023, Simon Fraser University News

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

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

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

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

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

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