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DBMS > EsgynDB vs. OpenQM vs. RavenDB vs. Vertica

System Properties Comparison EsgynDB vs. OpenQM vs. RavenDB vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonRavenDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionQpenQM is a high-performance, self-tuning, multi-value DBMSOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseCloud 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 DBMSMultivalue DBMSDocument storeRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
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
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.esgyn.cnwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmravendb.netwww.vertica.com
Technical documentationravendb.net/­docsvertica.com/­documentation
DeveloperEsgynRocket Software, originally Martin PhillipsHibernating RhinosOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015199320102005
Current release3.4-125.4, July 202212.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2, extended commercial license availableOpen Source infoAGPL version 3, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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++, JavaC#C++
Server operating systemsLinuxAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
Data schemeyesyes infowith some exceptionsschema-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 dateyesnoyes
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
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnoSQL-like query language (RQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
ADO.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
Basic
C
Java
Objective C
PHP
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresyesyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingyesShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesMulti-source replicationMulti-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 methodsyesnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID, Cluster-wide transaction availableACID
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAuthorization levels configured per client per databasefine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EsgynDBOpenQM infoalso called QMRavenDBVertica 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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
EsgynDBOpenQM infoalso called QMRavenDBVertica infoOpenText™ Vertica™
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