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DBMS > EsgynDB vs. GigaSpaces vs. Vertica vs. Yanza

System Properties Comparison EsgynDB vs. GigaSpaces vs. Vertica vs. Yanza

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsCloud 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.Time Series DBMS for IoT Applications
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infoColumn orientedTime Series DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial 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
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.esgyn.cnwww.gigaspaces.comwww.vertica.comyanza.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlvertica.com/­documentation
DeveloperEsgynGigaspaces TechnologiesOpenText infopreviously Micro Focus and Hewlett PackardYanza
Initial release2015200020052015
Current release15.5, September 202012.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercial infoLimited community edition freecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJava, C++, .NetC++
Server operating systemsLinuxLinux
macOS
Solaris
Windows
LinuxWindows
Data schemeyesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.schema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nono infoXML can be used for describing objects metadatanono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.no
SQL infoSupport of SQLyesSQL-99 for query and DML statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsADO.NET
JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C++
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
any language that supports HTTP calls
Server-side scripts infoStored proceduresJava Stored Proceduresyesyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersnoyes, event driven architectureyes, called Custom Alertsyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoMap-Reduce pattern can be built with XAP task executorsno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashno
More information provided by the system vendor
EsgynDBGigaSpacesVertica infoOpenText™ Vertica™Yanza
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...
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More resources
EsgynDBGigaSpacesVertica infoOpenText™ Vertica™Yanza
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