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DBMS > Microsoft Azure Synapse Analytics vs. Tarantool vs. WakandaDB vs. XTDB

System Properties Comparison Microsoft Azure Synapse Analytics vs. Tarantool vs. WakandaDB vs. XTDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTarantool  Xexclude from comparisonWakandaDB  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access dataA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS
Object oriented DBMSDocument store
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score0.10
Rank#356  Overall
#17  Object oriented DBMS
Score0.18
Rank#332  Overall
#46  Document stores
Websiteazure.microsoft.com/­services/­synapse-analyticswww.tarantool.iowakanda.github.iogithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationdocs.microsoft.com/­azure/­synapse-analyticswww.tarantool.io/­en/­docwakanda.github.io/­docwww.xtdb.com/­docs
DeveloperMicrosoftVKWakanda SASJuxt Ltd.
Initial release2016200820122019
Current release2.10.0, May 20222.7.0 (April 29, 2019), April 20191.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoAGPLv3, extended commercial license availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C++, JavaScriptClojure
Server operating systemshostedBSD
Linux
macOS
Linux
OS X
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyesschema-free
Typing infopredefined data types such as float or dateyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyesyes, extensible-data-notation format
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 indexesyesyesyes
SQL infoSupport of SQLyesFull-featured ANSI SQL supportnolimited SQL, making use of Apache Calcite
APIs and other access methodsADO.NET
JDBC
ODBC
Open binary protocolRESTful HTTP APIHTTP REST
JDBC
Supported programming languagesC#
Java
PHP
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
JavaScriptClojure
Java
Server-side scripts infoStored proceduresTransact SQLLua, C and SQL stored proceduresyesno
Triggersnoyes, before/after data modification events, on replication events, client session eventsyesno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.nonenone
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)
noneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 Consistency
Foreign keys infoReferential integrityno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, cooperative multitaskingyesyes
Durability infoSupport for making data persistentyesyes, write ahead loggingyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
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 persistenceno
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
yes

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More resources
Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTarantoolWakandaDBXTDB infoformerly named Crux
DB-Engines blog posts

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

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