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DBMS > Dgraph vs. EsgynDB vs. OpenQM vs. Vertica

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

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Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionQpenQM is a high-performance, self-tuning, multi-value DBMSCloud 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 modelGraph DBMSRelational DBMSMultivalue DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitedgraph.iowww.esgyn.cnwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.vertica.com
Technical documentationdgraph.io/­docsvertica.com/­documentation
DeveloperDgraph Labs, Inc.EsgynRocket Software, originally Martin PhillipsOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2016201519932005
Current release3.4-1212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPLv2, extended 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 languageGoC++, JavaC++
Server operating systemsLinux
OS X
Windows
LinuxAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Linux
Data schemeschema-freeyesyes infowith some exceptionsYes, 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 dateyesyesyes
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.nonoyesno
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
Basic
C
Java
Objective C
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoJava Stored Proceduresyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyesShardingyeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersyesMulti-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 methodsnoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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 controlno infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights can be defined down to the item levelfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DgraphEsgynDBOpenQM infoalso called QMVertica 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
DgraphEsgynDBOpenQM infoalso called QMVertica infoOpenText™ Vertica™
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