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DBMS > AlaSQL vs. Atos Standard Common Repository vs. Interbase vs. Microsoft Azure Data Explorer vs. Vertica

System Properties Comparison AlaSQL vs. Atos Standard Common Repository vs. Interbase vs. Microsoft Azure Data Explorer vs. Vertica

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonInterbase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionJavaScript DBMS libraryHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksLight-weight proven RDBMS infooriginally from BorlandFully managed big data interactive analytics platformCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Relational DBMSRelational DBMS infocolumn orientedRelational DBMS infoColumn oriented
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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitealasql.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.embarcadero.com/­products/­interbaseazure.microsoft.com/­services/­data-explorerwww.vertica.com
Technical documentationgithub.com/­AlaSQL/­alasqldocs.embarcadero.com/­products/­interbasedocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperAndrey Gershun & Mathias R. WulffAtos Convergence CreatorsEmbarcaderoMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20142016198420192005
Current release1703InterBase 2020, December 2019cloud service with continuous releases12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoMIT-Licensecommercialcommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptJavaCC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)LinuxAndroid
iOS
Linux
OS X
Windows
hostedLinux
Data schemeschema-freeSchema and schema-less with LDAP viewsyesFixed schema with schema-less datatypes (dynamic)Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenooptionalyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.noyesno infoexport as XML data possibleyesno
Secondary indexesnoyesyesall fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.noyesKusto Query Language (KQL), SQL subsetFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJavaScript APILDAPADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaScriptAll languages with LDAP bindings.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes infoInterbase procedure and trigger languageYes, possible languages: KQL, Python, Ryes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesInterbase Change Viewsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageAtomic execution of specific operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesnono
User concepts infoAccess controlnoLDAP bind authenticationfine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
AlaSQLAtos Standard Common RepositoryInterbaseMicrosoft Azure Data ExplorerVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
AlaSQLAtos Standard Common RepositoryInterbaseMicrosoft Azure Data ExplorerVertica infoOpenText™ Vertica™
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