What is a Graph Database? Why choose Neo4J among the other Graph Databases
You should first understand about Graph Database before answering the question “Why choose Neo4J among the other graph databases”.Graph Database is simply a Database Engine that models both Nodes and Edges in the relational Graph as first-class entities. This allows you to represent complex interactions between your data in a much more natural form and often allows for a closer fit to the real-world data that you are working with.
Graph Databases also often allow us to apply Graph Theory to our data in an efficient manner, allowing us to discover connections from our data that are otherwise difficult to see. For example, minimal routes between nodes, or disjoint sets of our data.
- Flexibility in updating and extending data
- Flexibility in updating and extending data
- Fast relationship-based searches
- Faster access to naturally indexed Graph Database
- Graph databases are not optimized to store and retrieve business entities
- It does not provide advanced match and survivorship functionality or data quality capabilities.
- Graph databases do not create better relationships.
- Some graph databases are limited to a single node and cannot scale beyond a certain point.
- Graph databases are not optimized for large-volume analytics queries typical of data warehousing.
Neo4j is used today by hundreds of thousands of companies and organizations in almost all industries like matchmaking, network management, software analytics, scientific research, routing, organizational and project management, recommendations, social networks, and more. Neo4j provides full database characteristics including ACID transaction compliance, cluster support, and runtime failover, making it suitable to use graph data in production scenarios.
Some particular features that made Neo4j very popular among users, developers, and DBAs and also answers the question “Why choose Neo4j”:
- Materializing of relationships at creation time, with no penalties for complex runtime queries
- Efficient representation of nodes and relationships enabling constant time traversals for relationships in the graph both in depth and in breadth
- All relationships in Neo4j are equally important and fast, which makes it possible to materialize and use new relationships to speed up the domain data when new needs arise
- Compressed storage and memory stashing for graphs, generating efficient scale-up and billions of nodes in one database on moderate hardware
- Neo4j is written and implemented in Java language using JVM.
Best practices neo4:
- Use a Rich Data Model: Rich Data Model includes a more associated understanding about structured data, expressive power, and fast traversals. It allows modeling a database with graph database that enables to translate drawing into a few expressions, add some conditions and constraints
- Use Cypher — Carefully: Cypher is a declarative graph query language that allows for expressive and efficient querying and updating of a property graph. Neo4j has its own query language called Cypher, which uses a similar syntax to SQL (Structured Query Language)
- Do Performance Testing: It is also essential at times to run database jobs to analyze how queries, operations, and the database itself is performing apart from the validity and correctness of your code units. These include mission critical operations such as financial analytics, banking, and real-time datasets, where errors can be disastrous
- Tune the Server Configuration: Neo4j tuning is considered during performance tuning a server, including general server load, memory and file contention, and even garbage collection penalties on the JVM. Under the Database Tuning tab, we can modify our tuning configurations as well as our cache sizing.
- Get a Cluster Running: When you are working with Neo4j, to enable optimization there are certain clusters better at accepting writes, while others are better for readers.Neo4j scales for big data with Neo4j Clustering. The cluster management layer continuously stays in sync with all instances in the cluster. It keeps track of any instances joining or leaving the cluster.
- Have a Relationship with the Neo4j Team: It’s very easy to get in touch with the Neo4j team. They will be with you in your Neo4j journey to help you succeed. Their aim is to provide enable organization & people to unlock the business value of connections, influences, and relationships in data through applications that can help business adapt the changing needs of its environment.
Neo4j is designed for linking relationships with speed, ease, and extreme flexibility. Apart from social networking and recommendations systems, common applications for Neo4j include asset management, network management, master data management, and identity-based access control. With Neo4j it’s really easy to translate a mental model directly into a database schema.
If you have to deal with densely connected data, use Neo4j. If you are experimenting with various conceptual models of your data, Neo4j is easier to work with than SQL databases.