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DBMS > Amazon DocumentDB vs. Microsoft Azure AI Search vs. Tarantool vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure AI Search vs. Tarantool vs. Yaacomo

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonTarantool  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceSearch-as-a-service for web and mobile app developmentIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeSearch engineDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsVector DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score5.71
Rank#64  Overall
#8  Search engines
Score1.67
Rank#150  Overall
#25  Document stores
#25  Key-value stores
#69  Relational DBMS
Websiteaws.amazon.com/­documentdbazure.microsoft.com/­en-us/­services/­searchwww.tarantool.ioyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourceslearn.microsoft.com/­en-us/­azure/­searchwww.tarantool.io/­en/­doc
DeveloperMicrosoftVKQ2WEB GmbH
Initial release2019201520082009
Current releaseV12.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++
Server operating systemshostedhostedBSD
Linux
macOS
Android
Linux
Windows
Data schemeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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 indexesyesyesyesyes
SQL infoSupport of SQLnonoFull-featured ANSI SQL supportyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIOpen binary protocolJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Java
JavaScript
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoLua, C and SQL stored procedures
Triggersnonoyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes infoImplicit feature of the cloud serviceAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 infotypically not used, however similar functionality with DBRef possiblenoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistenceyes
User concepts infoAccess controlAccess rights for users and rolesyes infousing Azure authenticationAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBMicrosoft Azure AI SearchTarantoolYaacomo
DB-Engines blog posts

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

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