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DBMS > Microsoft Azure AI Search vs. Sqrrl vs. Tarantool vs. ToroDB

System Properties Comparison Microsoft Azure AI Search vs. Sqrrl vs. Tarantool vs. ToroDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonSqrrl  Xexclude from comparisonTarantool  Xexclude from comparisonToroDB  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSearch-as-a-service for web and mobile app developmentAdaptable, secure NoSQL built on Apache AccumuloIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Document store
Key-value store
Relational DBMS
Document store
Secondary database modelsVector DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.59
Rank#63  Overall
#7  Search engines
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchsqrrl.comwww.tarantool.iogithub.com/­torodb/­server
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchwww.tarantool.io/­en/­doc
DeveloperMicrosoftAmazon infooriginally Sqrrl Data, Inc.VK8Kdata
Initial release2015201220082016
Current releaseV12.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoAGPL-V3
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 languageJavaC and C++Java
Server operating systemshostedLinuxBSD
Linux
macOS
All OS with a Java 7 VM
Data schemeyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsschema-free
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes infostring, integer, double, boolean, date, object_id
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLnonoFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP APIAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Open binary protocol
Supported programming languagesC#
Java
JavaScript
Python
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
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 eventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infomaking use of HadoopSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceselectable replication factor infomaking use of HadoopAsynchronous 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 methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Casual 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
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic updates per row, document, or graph entityACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsno
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 persistence
User concepts infoAccess controlyes infousing Azure authenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Access rights for users and roles

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More resources
Microsoft Azure AI SearchSqrrlTarantoolToroDB
DB-Engines blog posts

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

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