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DBMS > GridDB vs. Neo4j vs. Vertica

System Properties Comparison GridDB vs. Neo4j vs. Vertica

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonNeo4j  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsCloud 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 modelTime Series DBMSGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score44.47
Rank#23  Overall
#1  Graph DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitegriddb.netneo4j.comwww.vertica.com
Technical documentationdocs.griddb.netneo4j.com/­docsvertica.com/­documentation
DeveloperToshiba CorporationNeo4j, Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release201320072005
Current release5.1, August 20225.18.1, March 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version3, commercial licenses 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

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageC++Java, ScalaC++
Server operating systemsLinuxLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
Data schemeyesschema-free and schema-optionalYes, 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 dateyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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 indexesyesyes infopluggable indexing subsystem, by default Apache LuceneNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoUser defined Procedures and Functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes infovia event handleryes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingyes using Neo4j Fabrichorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-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 methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACID
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 can be defined per databaseUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
GridDBNeo4jVertica infoOpenText™ Vertica™
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Neo4j delivers graph technology that has been battle tested for performance and scale...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Neo4j is the market leader, graph database category creator, and the most widely...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGitHub trending repository
» more
Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
Cost-based models and subscription-based models are both available. One license is...
» more
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