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DBMS > AnzoGraph DB vs. RavenDB vs. Vertica

System Properties Comparison AnzoGraph DB vs. RavenDB vs. Vertica

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonRavenDB  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 virtualizationOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseCloud 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
Document storeRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Spatial 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
Score2.92
Rank#101  Overall
#18  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitecambridgesemantics.com/­anzographravendb.netwww.vertica.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmravendb.net/­docsvertica.com/­documentation
DeveloperCambridge SemanticsHibernating RhinosOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201820102005
Current release2.3, January 20215.4, July 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoAGPL version 3, commercial license availablecommercial 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

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Implementation languageC#C++
Server operating systemsLinuxLinux
macOS
Raspberry Pi
Windows
Linux
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeYes, 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 datenoyes
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.nono
Secondary indexesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query language (RQL)Full 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
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
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#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source 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 loadingyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID, Cluster-wide transaction availableACID
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 rolesAuthorization levels configured per client per databasefine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
AnzoGraph DBRavenDBVertica 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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
AnzoGraph DBRavenDBVertica infoOpenText™ Vertica™
Recent citations in the news

AnzoGraph review: A graph database for deep analytics
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AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
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