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DBMS > Dragonfly vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Tarantool

System Properties Comparison Dragonfly vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Tarantool

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonNSDb  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 instanceElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelKey-value storeRelational DBMSTime Series DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#261  Overall
#38  Key-value stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
azure.microsoft.com/­services/­synapse-analyticsnsdb.iowww.tarantool.io
Technical documentationwww.dragonflydb.io/­docsdocs.microsoft.com/­azure/­synapse-analyticsnsdb.io/­Architecturewww.tarantool.io/­en/­doc
DeveloperDragonflyDB team and community contributorsMicrosoftVK
Initial release2023201620172008
Current release1.0, March 20232.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialOpen Source infoApache Version 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Java, ScalaC and C++
Server operating systemsLinuxhostedLinux
macOS
BSD
Linux
macOS
Data schemescheme-freeyesFlexible 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 arraysyesyes: int, bigint, decimal, stringstring, 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.nononono
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLnoyesSQL-like query languageFull-featured ANSI SQL support
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
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
C#
Java
PHP
Java
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresLuaTransact SQLnoLua, C and SQL stored procedures
Triggerspublish/subscribe channels provide some trigger functionalitynoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingSharding, 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 replicationyesAsynchronous 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 methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyCasual 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 integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDnoACID, 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 serveryesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlPassword-based authenticationyesAccess 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
DragonflyMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNSDbTarantool
DB-Engines blog posts

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

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