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DBMS > EsgynDB vs. Graph Engine vs. Hawkular Metrics vs. Tarantool

System Properties Comparison EsgynDB vs. Graph Engine vs. Hawkular Metrics vs. Tarantool

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTarantool  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.In-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSGraph DBMS
Key-value store
Time Series DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
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
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitewww.esgyn.cnwww.graphengine.iowww.hawkular.orgwww.tarantool.io
Technical documentationwww.graphengine.io/­docs/­manualwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.tarantool.io/­en/­doc
DeveloperEsgynMicrosoftCommunity supported by Red HatVK
Initial release2015201020142008
Current release2.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java.NET and CJavaC and C++
Server operating systemsLinux.NETLinux
OS X
Windows
BSD
Linux
macOS
Data schemeyesyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 indexesyesnoyes
SQL infoSupport of SQLyesnonoFull-featured ANSI SQL support
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIHTTP RESTOpen binary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
F#
Visual Basic
Go
Java
Python
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresJava Stored ProceduresyesnoLua, C and SQL stored procedures
Triggersnonoyes infovia Hawkular Alertingyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infobased on CassandraSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factor infobased on CassandraAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Casual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
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, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
EsgynDBGraph Engine infoformer name: TrinityHawkular MetricsTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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