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DBMS > Atos Standard Common Repository vs. Microsoft Azure Data Explorer vs. Tarantool vs. Yaacomo vs. YottaDB

System Properties Comparison Atos Standard Common Repository vs. Microsoft Azure Data Explorer vs. Tarantool vs. Yaacomo vs. YottaDB

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTarantool  Xexclude from comparisonYaacomo  Xexclude from comparisonYottaDB  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksFully managed big data interactive analytics platformIn-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 computingA fast and solid embedded Key-value store
Primary database modelDocument store
Key-value store
Relational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Relational DBMSKey-value store
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 extensionRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­services/­data-explorerwww.tarantool.ioyaacomo.comyottadb.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tarantool.io/­en/­docyottadb.com/­resources/­documentation
DeveloperAtos Convergence CreatorsMicrosoftVKQ2WEB GmbHYottaDB, LLC
Initial release20162019200820092001
Current release1703cloud service with continuous releases2.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterprisecommercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C
Server operating systemsLinuxhostedBSD
Linux
macOS
Android
Linux
Windows
Docker
Linux
Data schemeSchema and schema-less with LDAP viewsFixed schema with schema-less datatypes (dynamic)Flexible data schema: relational definition for tables with ability to store json-like documents in columnsyesschema-free
Typing infopredefined data types such as float or dateoptionalyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesstring, double, decimal, uuid, integer, blob, boolean, datetimeyesno
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.yesyesnonono
Secondary indexesyesall fields are automatically indexedyesyesno
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetFull-featured ANSI SQL supportyesby using the Octo plugin
APIs and other access methodsLDAPMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Open binary protocolJDBC
ODBC
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RLua, C and SQL stored procedures
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding 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 nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
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
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, full featured in-memory storage engine with persistenceyesyes
User concepts infoAccess controlLDAP bind authenticationAzure Active Directory 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-standardUsers and groups based on OS-security mechanisms

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More resources
Atos Standard Common RepositoryMicrosoft Azure Data ExplorerTarantoolYaacomoYottaDB
DB-Engines blog posts

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

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