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DBMS > Microsoft Azure Synapse Analytics vs. NSDb vs. Tarantool vs. TDSQL for MySQL vs. WakandaDB

System Properties Comparison Microsoft Azure Synapse Analytics vs. NSDb vs. Tarantool vs. TDSQL for MySQL vs. WakandaDB

Editorial information provided by DB-Engines
NameMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonNSDb  Xexclude from comparisonTarantool  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionElastic, 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 applicationsA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSTime Series DBMSDocument store
Key-value store
Relational DBMS
Relational DBMSObject oriented DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extensionDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteazure.microsoft.com/­services/­synapse-analyticsnsdb.iowww.tarantool.iowww.tencentcloud.com/­products/­dcdbwakanda.github.io
Technical documentationdocs.microsoft.com/­azure/­synapse-analyticsnsdb.io/­Architecturewww.tarantool.io/­en/­docwww.tencentcloud.com/­document/­product/­1042wakanda.github.io/­doc
DeveloperMicrosoftVKTencentWakanda SAS
Initial release20162017200820132012
Current release2.10.0, May 20222.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterprisecommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, ScalaC and C++C++, JavaScript
Server operating systemshostedLinux
macOS
BSD
Linux
macOS
hostedLinux
OS X
Windows
Data schemeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringstring, double, decimal, uuid, integer, blob, boolean, datetimeyesyes
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.nonononono
Secondary indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyesSQL-like query languageFull-featured ANSI SQL supportyesno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
Open binary protocolJDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Java
PHP
Java
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Java
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresTransact SQLnoLua, C and SQL stored proceduresyesyes
Triggersnoyes, before/after data modification events, on replication events, client session eventsyesyes
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.Automatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes, write ahead loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, full featured in-memory storage engine with persistencenono
User concepts infoAccess controlyesAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Users with fine-grained authorization conceptyes

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More resources
Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNSDbTarantoolTDSQL for MySQLWakandaDB
DB-Engines blog posts

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

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