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DBMS > EsgynDB vs. etcd vs. Graph Engine vs. Vertica

System Properties Comparison EsgynDB vs. etcd vs. Graph Engine vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonetcd  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA distributed reliable key-value storeA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineCloud 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 storeGraph DBMS
Key-value store
Relational 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
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.esgyn.cnetcd.io
github.com/­etcd-io/­etcd
www.graphengine.iowww.vertica.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.graphengine.io/­docs/­manualvertica.com/­documentation
DeveloperEsgynMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201520102005
Current release3.4, August 201912.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoMIT Licensecommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaGo.NET and CC++
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
.NETLinux
Data schemeyesschema-freeyesYes, 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.nononono
Secondary indexesyesnoNo 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
gRPC
JSON over HTTP
RESTful 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++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
F#
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresnoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, watching key changesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.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 methodsyesnono 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 dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EsgynDBetcdGraph Engine infoformer name: TrinityVertica 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...
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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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More resources
EsgynDBetcdGraph Engine infoformer name: TrinityVertica infoOpenText™ Vertica™
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