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DBMS > Brytlyt vs. CrateDB vs. Dragonfly vs. ToroDB

System Properties Comparison Brytlyt vs. CrateDB vs. Dragonfly vs. ToroDB

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonCrateDB  Xexclude from comparisonDragonfly  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLDistributed 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 instanceA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeDocument store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Websitebrytlyt.iocratedb.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
github.com/­torodb/­server
Technical documentationdocs.brytlyt.iocratedb.com/­docswww.dragonflydb.io/­docs
DeveloperBrytlytCrateDragonflyDB team and community contributors8Kdata
Initial release2016201320232016
Current release5.0, August 20231.0, March 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoBSL 1.1Open Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageC, C++ and CUDAJavaC++Java
Server operating systemsLinux
OS X
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxAll OS with a Java 7 VM
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)scheme-freeschema-free
Typing infopredefined data types such as float or dateyesyesstrings, hashes, lists, sets, sorted sets, bit arraysyes infostring, integer, double, boolean, date, object_id
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.yes infospecific XML-type available, but no XML query functionality.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protocol
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.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
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functions (Javascript)Lua
Triggersyesnopublish/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 nodesSource-replica replicationConfigurable replication on table/partition-levelSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyAtomic execution of command blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, strict serializability by the serveryes
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.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardrights management via user accountsPassword-based authenticationAccess rights for users and roles
More information provided by the system vendor
BrytlytCrateDBDragonflyToroDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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BrytlytCrateDBDragonflyToroDB
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