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DBMS > EsgynDB vs. Machbase Neo vs. Microsoft Azure AI Search vs. Vertica

System Properties Comparison EsgynDB vs. Machbase Neo vs. Microsoft Azure AI Search vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionTimeSeries DBMS for AIoT and BigDataSearch-as-a-service for web and mobile app developmentCloud 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 modelRelational DBMSTime Series DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsVector DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.esgyn.cnmachbase.comazure.microsoft.com/­en-us/­services/­searchwww.vertica.com
Technical documentationmachbase.com/­dbmslearn.microsoft.com/­en-us/­azure/­searchvertica.com/­documentation
DeveloperEsgynMachbaseMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201320152005
Current releaseV8.0, August 2023V112.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial infofree test version availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesno 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 languageC++, JavaCC++
Server operating systemsLinuxLinux
macOS
Windows
hostedLinux
Data schemeyesyesyesYes, 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 dateyesyesyesyes
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.nononono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-like query languagenoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
C#
Java
JavaScript
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factoryes infoImplicit feature of the cloud serviceMulti-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 methodsyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infovolatile and lookup tablenono
User concepts infoAccess controlfine grained access rights according to SQL-standardsimple password-based access controlyes infousing Azure authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EsgynDBMachbase Neo infoFormer name was InfinifluxMicrosoft Azure AI SearchVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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...
» more

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EsgynDBMachbase Neo infoFormer name was InfinifluxMicrosoft Azure AI SearchVertica infoOpenText™ Vertica™
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