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DBMS > IBM Cloudant vs. Microsoft Azure Data Explorer vs. Quasardb vs. Tarantool vs. TimesTen

System Properties Comparison IBM Cloudant vs. Microsoft Azure Data Explorer vs. Quasardb vs. Tarantool vs. TimesTen

Editorial information provided by DB-Engines
NameIBM Cloudant  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuasardb  Xexclude from comparisonTarantool  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionDatabase as a Service offering based on Apache CouchDBFully managed big data interactive analytics platformDistributed, high-performance timeseries databaseIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsIn-Memory RDBMS compatible to Oracle
Primary database modelDocument storeRelational DBMS infocolumn orientedTime Series DBMSDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.68
Rank#106  Overall
#20  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.ibm.com/­products/­cloudantazure.microsoft.com/­services/­data-explorerquasar.aiwww.tarantool.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcloud.ibm.com/­docs/­Cloudantdocs.microsoft.com/­en-us/­azure/­data-explorerdoc.quasar.ai/­masterwww.tarantool.io/­en/­docdocs.oracle.com/­database/­timesten-18.1
DeveloperIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014MicrosoftquasardbVKOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20102019200920081998
Current releasecloud service with continuous releases3.14.1, January 20242.10.0, May 202211 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC++C and C++
Server operating systemshostedhostedBSD
Linux
OS X
Windows
BSD
Linux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or datenoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infointeger and binarystring, 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.noyesnonono
Secondary indexesyesall fields are automatically indexedyes infowith tagsyesyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like query languageFull-featured ANSI SQL supportyes
APIs and other access methodsRESTful HTTP/JSON APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP APIOpen binary protocolJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC#
Java
JavaScript
Objective-C
PHP
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresView functions (Map-Reduce) in JavaScriptYes, possible languages: KQL, Python, RnoLua, C and SQL stored proceduresPL/SQL
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.none
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with selectable replication factorAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate 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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a document possiblenoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic lockingyesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes, write ahead loggingyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoTransient modeyes, full featured in-memory storage engine with persistenceyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAzure Active Directory AuthenticationCryptographically strong user authentication and audit trailAccess 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
IBM CloudantMicrosoft Azure Data ExplorerQuasardbTarantoolTimesTen
DB-Engines blog posts

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

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