VonConsulting.ro - 10 ani de Recrutare si Oursourcing IT
  • Home
  • About Us
  • Servicesarrow_drop_down
    • Recruitment
    • Outsourcing
    • Temporary Staffing
    • Consultancy
  • Career Opportunities
  • Contact Us
  • arrow_drop_down
  • ro
  • en
  • de

Graph databases can design flexible hierarchies and be used in cloud deployment

August 11, 2020 - by Andreea Paleologu

Graph databases store information as nodes and data specifying their relationships with other nodes. They are architectures for storing data with complex relationships.

They have been substantially used, especially during the past decade, despite the fact that companies have considered other NoSQL and big data technologies.

The global graph database market was estimated at $651 million in 2018 and is expected to grow to $3.73 billion by 2026.

Competitors remain in the range of other big data management technologies, including Hadoop and Spark.

Graph databases and query languages

Developers think in objects and use hierarchical data representations in XML and JSON regularly.

For graph databases, although it may be relatively easy to comprehend the modeling of nodes and relationships used, querying them requires learning new practices and skills.

Developers can query Neo4j graph databases using Resource Description Framework (RDF) and Gremlin, but 90% prefer to use Cypher.

The query is elegant and efficient but has a learning curve for those used to writing SQL queries. Here’s one of the first challenges for organizations moving toward graph databases: SQL is a pervasive skill set, and Cypher and other graph query languages are a new skill to learn.

These databases can be used in flexible hierarchy design

Product catalogs, content management systems, project management applications, ERPs and CRMs all use hierarchies to categorize and tag information. Graph databases enable arbitrary hierarchies. Developers need to create different views of the hierarchy for different needs.

To take advantage of flexible hierarchies, it helps to design applications from the ground up with a graph database. The entire application is then designed based on querying the graph and leveraging the nodes, relationships, labels, and properties of the graph.

Databases and cloud deployment – reduced operational complexity

Deploying data management solutions into a data center has to consider infrastructure and operations, security requirements and review performance considerations. These are used to size up servers, storage, and networks. They are also used as replicated systems for redundancy and disaster recovery.

Organizations experimenting with graph databases now have several cloud options. Engineers can deploy Neo4j to GCP, AWS, Azure, or leverage Neo4j’s Aura, a database as a service.

The public cloud vendors have graph database capabilities. These include AWS Neptune, the Gremlin API in Azure’s CosmoDB, the open source JanusGraph on GCP, or the graph features in Oracle’s Cloud Database Services.

  • Recent Articles
    • System Engineering Expert NSX
    • How About Becoming a Back-End Developer?
    • The Fanciest Job in Software Engineering?… Yet the Most Sought For?
    • Manifesto for Agile Software Development
    • Behind the Scenes of An IT Recruiter’s Life
  • Recently Added Jobs
    • Platform Integration for Embedded Systems
    • TECHNICAL SUPPORT SPECIALIST
    • Senior Linux C/C++ Developer
    • Senior Linux C/C++ Userspace & Kernel Developer
    • .NET Developer – Dynamics Specialist (XRM)
  • Newsletter Signup

    Verificați inbox-ul sau fișierul spam al email-ului dvs. pentru a confirma abonarea.

© 2023 - VonConsulting.
  • Terms and Conditions
  • Privacy
Manage Cookie Preferences
To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions.
Functional Always active
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
Preferences
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
Statistics
The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
Marketing
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.
Manage options Manage services Manage vendors Read more about these purposes
Preferences
{title} {title} {title}