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DBMS > Apache Impala vs. Microsoft Azure AI Search vs. searchxml vs. Tarantool

System Properties Comparison Apache Impala vs. Microsoft Azure AI Search vs. searchxml vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonsearchxml  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopSearch-as-a-service for web and mobile app developmentDBMS for structured and unstructured content wrapped with an application serverIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSSearch engineNative XML DBMS
Search engine
Document store
Key-value store
Relational DBMS
Secondary database modelsDocument storeVector DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteimpala.apache.orgazure.microsoft.com/­en-us/­services/­searchwww.searchxml.net/­category/­productswww.tarantool.io
Technical documentationimpala.apache.org/­impala-docs.htmllearn.microsoft.com/­en-us/­azure/­searchwww.searchxml.net/­support/­handoutswww.tarantool.io/­en/­doc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftinformationpartners gmbhVK
Initial release2013201520152008
Current release4.1.0, June 2022V11.02.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen 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

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Implementation languageC++C++C and C++
Server operating systemsLinuxhostedWindowsBSD
Linux
macOS
Data schemeyesyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, 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.nonoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIRESTful HTTP API
WebDAV
XQuery
XSLT
Open binary protocol
Supported programming languagesAll languages supporting JDBC/ODBCC#
Java
JavaScript
Python
C++ infomost other programming languages supported via APIsC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoon the application serverLua, C and SQL stored procedures
Triggersnononoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneSharding, 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 nodesselectable replication factoryes infoImplicit feature of the cloud serviceyes infosychronisation to multiple collectionsAsynchronous 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 methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonomultiple readers, single writerACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes infousing Azure authenticationDomain, group and role-based access control at the document level and for application servicesAccess 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
Apache ImpalaMicrosoft Azure AI SearchsearchxmlTarantool
DB-Engines blog posts

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

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