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DBMS > Dragonfly vs. GigaSpaces vs. Tarantool

System Properties Comparison Dragonfly vs. GigaSpaces vs. Tarantool

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGigaSpaces  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelKey-value storeDocument store
Object oriented DBMS infoValues are user defined objects
Document store
Key-value store
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.gigaspaces.comwww.tarantool.io
Technical documentationwww.dragonflydb.io/­docsdocs.gigaspaces.com/­latest/­landing.htmlwww.tarantool.io/­en/­doc
DeveloperDragonflyDB team and community contributorsGigaspaces TechnologiesVK
Initial release202320002008
Current release1.0, March 202315.5, September 20202.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache Version 2; Commercial licenses availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .NetC and C++
Server operating systemsLinuxLinux
macOS
Solaris
Windows
BSD
Linux
macOS
Data schemescheme-freeschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 infoXML can be used for describing objects metadatano
Secondary indexesnoyesyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsFull-featured ANSI SQL support
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Open binary protocol
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
.Net
C++
Java
Python
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresLuayesLua, C and SQL stored procedures
Triggerspublish/subscribe channels provide some trigger functionalityyes, event driven architectureyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executors
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlPassword-based authenticationRole-based access controlAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
DragonflyGigaSpacesTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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