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DBMS > AllegroGraph vs. Amazon DocumentDB vs. Hawkular Metrics vs. Vitess

System Properties Comparison AllegroGraph vs. Amazon DocumentDB vs. Hawkular Metrics vs. Vitess

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonAmazon DocumentDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#204  Overall
#35  Document stores
#18  Graph DBMS
#7  RDF stores
#10  Vector DBMS
Score1.91
Rank#124  Overall
#22  Document stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.86
Rank#202  Overall
#95  Relational DBMS
Websiteallegrograph.comaws.amazon.com/­documentdbwww.hawkular.orgvitess.io
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlaws.amazon.com/­documentdb/­resourceswww.hawkular.org/­hawkular-metrics/­docs/­user-guidevitess.io/­docs
DeveloperFranz Inc.Community supported by Red HatThe Linux Foundation, PlanetScale
Initial release2004201920142013
Current release8.0, December 202315.0.2, December 2022
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
Docker
Linux
macOS
Data schemeyes infoRDF schemasschema-freeschema-freeyes
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.no infobulk load of XML files possiblenono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSPARQL is used as query languagenonoyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP API
SPARQL
proprietary protocol using JSON (MongoDB compatible)HTTP RESTADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Go
Java
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnonoyes infoproprietary syntax
Triggersyesnoyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodeswith FederationnoneSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possiblenoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-document operationsnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and rolesnoUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
AllegroGraphAmazon DocumentDBHawkular MetricsVitess
News

AllegroGraph Named a 2024 Trend Setting Product
16 September 2024

Gartner recognized Franz Inc. as a Key Neuro-Symbolic AI Provider in 2024 Hype Cycle for AI
10 September 2024

Next-Generation Cybersecurity: Integrating Knowledge Graphs and Neuro-Symbolic AI with STIX and TAXII
10 September 2024

Pruning Cycles in UMLS Metathesaurus: A Neuro Symbolic AI Approach
9 September 2024

Podcast – Gartner AI Hype Cycle – Knowledge Graphs and Neuro-Symbolic AI
24 August 2024

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More resources
AllegroGraphAmazon DocumentDBHawkular MetricsVitess
Recent citations in the news

Neuro-Symbolic AI: The Peak of Artificial Intelligence
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8 April 2024, TDWI

Franz Releases the First Neuro-Symbolic AI Platform Merging Knowledge Graphs, Generative AI, and Vector Storage
11 December 2023, Datanami

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Deepthi Sigireddi on Distributed Database Architecture in the Cloud Native Era
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