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DBMS > Dgraph vs. EsgynDB vs. Vertica vs. YDB

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

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Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionCloud 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.A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelGraph DBMSRelational DBMSRelational DBMS infoColumn orientedDocument store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitedgraph.iowww.esgyn.cnwww.vertica.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdgraph.io/­docsvertica.com/­documentationydb.tech/­en/­docs
DeveloperDgraph Labs, Inc.EsgynOpenText infopreviously Micro Focus and Hewlett PackardYandex
Initial release2016201520052019
Current release12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infoLimited community edition freeOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++, JavaC++
Server operating systemsLinux
OS X
Windows
LinuxLinuxLinux
Data schemeschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.Flexible Schema (defined schema, partial schema, schema free)
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 indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLnoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.SQL-like query language (YQL)
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
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyesShardinghorizontal partitioning, hierarchical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Active-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
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.nonono
User concepts infoAccess controlno infoPlanned for future releasesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashAccess rights defined for Yandex Cloud users
More information provided by the system vendor
DgraphEsgynDBVertica infoOpenText™ Vertica™YDB
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...
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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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DgraphEsgynDBVertica infoOpenText™ Vertica™YDB
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