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DBMS > Dragonfly vs. Drizzle vs. Splice Machine vs. SQL.JS vs. Sqrrl

System Properties Comparison Dragonfly vs. Drizzle vs. Splice Machine vs. SQL.JS vs. Sqrrl

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonDrizzle  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQL.JS  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.
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPort of SQLite to JavaScriptAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.53
Rank#252  Overall
#116  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
splicemachine.comsql.js.orgsqrrl.com
Technical documentationwww.dragonflydb.io/­docssplicemachine.com/­how-it-workssql.js.org/­documentation/­index.html
DeveloperDragonflyDB team and community contributorsDrizzle project, originally started by Brian AkerSplice MachineAlon Zakai infoenhancements implemented by othersAmazon infooriginally Sqrrl Data, Inc.
Initial release20232008201420122012
Current release1.0, March 20237.2.4, September 20123.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoGNU GPLOpen Source infoAGPL 3.0, commercial license availableOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++JavaJavaScriptJava
Server operating systemsLinuxFreeBSD
Linux
OS X
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemescheme-freeyesyesyesschema-free
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesyesyes
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 indexesnoyesyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsyesyes infoSQL-92 is not fully supportedno
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolJDBCJDBC
Native Spark Datasource
ODBC
JavaScript APIAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
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++
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScriptActionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresLuanoyes infoJavanono
Triggerspublish/subscribe channels provide some trigger functionalityno infohooks for callbacks inside the server can be used.yesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar PartitioningnoneSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
noneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencynoneImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDACIDACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesno infoexcept by serializing a db to a fileyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlPassword-based authenticationPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standardnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
DragonflyDrizzleSplice MachineSQL.JSSqrrl
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