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DBMS > EsgynDB vs. Memcached vs. Microsoft Azure Table Storage vs. Vertica

System Properties Comparison EsgynDB vs. Memcached vs. Microsoft Azure Table Storage vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionIn-memory key-value store, originally intended for cachingA Wide Column Store for rapid development using massive semi-structured datasetsCloud 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 DBMSKey-value storeWide column storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.esgyn.cnwww.memcached.orgazure.microsoft.com/­en-us/­services/­storage/­tableswww.vertica.com
Technical documentationgithub.com/­memcached/­memcached/­wikivertica.com/­documentation
DeveloperEsgynDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015200320122005
Current release1.6.27, May 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercialcommercial 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 systemsLinuxFreeBSD
Linux
OS X
Unix
Windows
hostedLinux
Data schemeyesschema-freeschema-freeYes, 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 dateyesnoyesyes
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.nonono
Secondary indexesyesnonoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
Proprietary protocolRESTful 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.Net.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
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 nodesShardingnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnone infoRepcached, a Memcached patch, provides this functionallityyes 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 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 dataACIDnooptimistic lockingACID
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing SASL (Simple Authentication and Security Layer) protocolAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EsgynDBMemcachedMicrosoft Azure Table StorageVertica 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...
» more
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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EsgynDBMemcachedMicrosoft Azure Table StorageVertica infoOpenText™ Vertica™
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