Supports open graph APIs
It supports open graph APIs for both Gremlin and SPARQL, and offers great performance for both of these graph models and their query languages. It allows you select the Property Graph model and its open source query language, the W3C standard Resource Description Framework (RDF) model or the Apache TinkerPop Gremlin or and its standard query language, SPARQL.
High performance and scalability
It is a high-performance graph, purpose-built database. It enhances the processing graph queries. Neptune supports up to 15 low latency read replicas across 3 Availability Zones to scale read capacity and perform beyond one-hundred thousand graph queries/ second. You can simply scale your database deployment up and down from lesser to larger instance types as your requirements change.
High availability and durability
It is extremely accessible, durable, and ACID (Atomicity, Consistency, Isolation, Durability) compliant. Neptune is created to offer greater than 99.99% availability. It features fault-tolerant and self-healing storage created for the cloud that duplicates 6 copies of your data across 3 Availability Zones. Neptune incessantly backs up your data to Amazon S3, and clearly regains from physical storage failures. For High accessibility, instance failover normally takes less than 30 seconds.
It offers various levels of security for your database, containing network isolation using Amazon VPC, HTTPS encrypted client connections, support for IAM authentication for endpoint access, encryption at rest with the use of keys you build and manage via AWS Key Management Service (KMS). On an encrypted Neptune instance, data in the core storage is encrypted, as are the automated backups, snapshots, and imitation in the same cluster.
You don’t have to worry about database management tasks with Amazon Neptune, like hardware provisioning, setup, software patching, configuration, or backups. Neptune automatically and incessantly monitors and backs up your database to Amazon S3, allowing granular point-in-time recovery. You can watch database performance with the use of Amazon CloudWatch.
When to use graph databases
Graph databases, such as Amazon Neptune, are purpose-built to store and navigate relationships. They have benefits over relational databases for use cases such as recommendation engines, social networking and fraud detection, where you required to build a relationships between data and quickly query these relationships. There are many challenges to building these types of applications with the use of relational database. You would require various tables with numerous foreign keys. SQL queries to navigate this data would need nested queries and intricate joins that rapidly become unwieldy, and as your data size grows over time, the queries would not perform well.
It uses graph structures like edges (relationships), nodes (data entities) and properties to signify and store data. The relationships are stored as1st order citizens of the data model. This enables data in nodes to be straightly connected, dramatically enhancing the performance of queries that navigate relationships in the data. Neptune’s interactive performance at scale efficiently allows a wide set of graph use cases.
So these are some benefits of Amazon Neptune and we are sure that your all doubts and questions related to its advantages have been cleared. For more details and implementation of the technology you can contact Kalibroida. We are here to help you at any time with all the queries related to AWS products. Our expert professionals are working on it and know everything about it. So, if you have any doubt or you want to avail the technology than you just have to contact us and we will offer you the most satisfactory services.