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DBMS > EsgynDB vs. Graph Engine vs. Hawkular Metrics vs. LevelDB vs. Microsoft Azure Cosmos DB

System Properties Comparison EsgynDB vs. Graph Engine vs. Hawkular Metrics vs. LevelDB vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesGlobally distributed, horizontally scalable, multi-model database service
Primary database modelRelational DBMSGraph DBMS
Key-value store
Time Series DBMSKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Websitewww.esgyn.cnwww.graphengine.iowww.hawkular.orggithub.com/­google/­leveldbazure.microsoft.com/­services/­cosmos-db
Technical documentationwww.graphengine.io/­docs/­manualwww.hawkular.org/­hawkular-metrics/­docs/­user-guidegithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdlearn.microsoft.com/­azure/­cosmos-db
DeveloperEsgynMicrosoftCommunity supported by Red HatGoogleMicrosoft
Initial release20152010201420112014
Current release1.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java.NET and CJavaC++
Server operating systemsLinux.NETLinux
OS X
Windows
Illumos
Linux
OS X
Windows
hosted
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes infoJSON types
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 indexesyesnonoyes infoAll properties auto-indexed by default
SQL infoSupport of SQLyesnononoSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIHTTP RESTDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
F#
Visual Basic
Go
Java
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Server-side scripts infoStored proceduresJava Stored ProceduresyesnonoJavaScript
Triggersnonoyes infovia Hawkular AlertingnoJavaScript
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infobased on CassandranoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factor infobased on Cassandranoneyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoMulti-item ACID transactions with snapshot isolation within a partition
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes infowith automatic compression on writesyes
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-standardnonoAccess rights can be defined down to the item level

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More resources
EsgynDBGraph Engine infoformer name: TrinityHawkular MetricsLevelDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
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