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DBMS > AnzoGraph DB vs. Brytlyt vs. Vertica

System Properties Comparison AnzoGraph DB vs. Brytlyt vs. Vertica

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonBrytlyt  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLCloud 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 modelGraph DBMS
RDF store
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitecambridgesemantics.com/­anzographbrytlyt.iowww.vertica.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.brytlyt.iovertica.com/­documentation
DeveloperCambridge SemanticsBrytlytOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201820162005
Current release2.3, January 20215.0, August 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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, C++ and CUDAC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
Data schemeSchema-free and OWL/RDFS-schema supportyesYes, 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 dateyesyes
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.noyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Java
Python
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions infoin PL/pgSQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterSource-replica replicationMulti-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 methodsKerberos/HDFS data loadingnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
AnzoGraph DBBrytlytVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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...
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More resources
AnzoGraph DBBrytlytVertica infoOpenText™ Vertica™
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