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DBMS > CockroachDB vs. Dragonfly vs. Google Cloud Datastore vs. Sequoiadb

System Properties Comparison CockroachDB vs. Dragonfly vs. Google Cloud Datastore vs. Sequoiadb

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Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonDragonfly  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformNewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSKey-value storeDocument storeDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitewww.cockroachlabs.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­datastorewww.sequoiadb.com
Technical documentationwww.cockroachlabs.com/­docswww.dragonflydb.io/­docscloud.google.com/­datastore/­docswww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperCockroach LabsDragonflyDB team and community contributorsGoogleSequoiadb Ltd.
Initial release2015202320082013
Current release24.1.0, May 20241.0, March 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availableOpen Source infoBSL 1.1commercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++C++
Server operating systemsLinux
macOS
Windows
LinuxhostedLinux
Data schemedynamic schemascheme-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyes, details hereyes infooid, date, timestamp, binary, regex
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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes, wire compatible with PostgreSQLnoSQL-like query language (GQL)SQL-like query language
APIs and other access methodsJDBCProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
RESTful HTTP/JSON API
proprietary protocol using JSON
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
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
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoLuausing Google App EngineJavaScript
Triggersnopublish/subscribe channels provide some trigger functionalityCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTSource-replica replicationMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes
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.noyesnono
User concepts infoAccess controlRole-based access controlPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control

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More resources
CockroachDBDragonflyGoogle Cloud DatastoreSequoiadb
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