Apache HBase vs. Neo4j

HBase is well suited for streaming ingest, fast lookups, massive datasets, data warehouse lookup tables, RDBMS replacement, MongoDB replacement, key-value store, data scans, logs, JSON storage and some binary storage. My preferred use case is for storing data points like time series or data produced by sensors. I often use HBase when I need data available immediately and I am not looking for transactions. This is a great store for really wide tables with tons of columns. It is also great if you are not sure what type of data you are going to have. It really excels at sparse data.

Incentivized

Its very well suited for storing graph types relationship information, such as a group of people and their relationships. Data modeling this sort of information in a traditional SQL database is a pain and inefficient. Using Neo4J allows for efficient modeling of data while providing rich querying capabilities using Cypher. Its also a great fit for any programming language because of its support for REST API. It's less appropriate for any other data structure other than Graph data. So as with any DB, evaluate the data structure and query and if the querying revolves around relationships, then Neo4J is a fit. If there is more need for looking up individual nodes and their associated information, Neo4J might not be the most efficient solution in the market.

Incentivized

• Scalable and truly non-relational data
• HBase operations run in real-time on its database rather than MapReduce jobs
• Scales linearly to support billions of rows with millions of columns

Incentivized

• When joins are a common in a relational store, switching to Neo4j is better
• When pattern matching and surfacing interesting insights is the goal, neo4j's cypher is pretty powerful
• When schema is not completely known beforehand and needs to be evolved with time

Incentivized

• Write performance
• Performance support for parquet file format. supports, but performance wise still not there
• API / library availability for spark, rather than creating a new library for it

Incentivized

• It would be nice to have some concept of namespaces, or some way of roughly making a single instance multi-tenant. It'd be nice to make sandboxing easier.
• Automatic backups could be improved.

Incentivized

There's really not anything else out there that I've seen comparable for my use cases. HBase has never proven me wrong. Some companies align their whole business on HBase and are moving all of their infrastructure from other database engines to HBase. It's also open source and has a very collaborative community.

Incentivized

[Based on] Query Language, Performance on small and large data sets, integration and deployment, analysis, API support, Interactive UI.

Incentivized

Compared NoSQL databases with traditional databases for faster retrieval and consistency. As MongoDB is a NoSQL supports dynamic fields, however, query performance is bad for aggregations and added maintenance. When compared with MySQL and Teradata, it could not scale up as fast as Hbase and added cost involved to it. HBase can be easily scalable to a huge volume of records, have a faster lookup and provides consistency

Incentivized

I have not used anything like Neo4J because of how unique it is in the work that it allows me to do. I am not aware of any other graph database platforms and it might be because it is a growing area (especially in the world of pharmaceuticals). I would be open to trying other softwares though.

Incentivized

• Positive: Open source, easy to use, good to store big data.
• Negative: SQL functionalities are not available.
• More memory utilization
• More troubleshooting

Incentivized

• For experimentation purposes, it had a positive impact on my company. It was very natural to work with Neo4j and so intuitive to visualize the data.
• Neo4j community edition is free, which is what we experimented on. So there was no investment up front apart from employee's time. But this quickly gave results and it was time well spent.
• Neo4j is a cool but very new technology. It was hard to have people onboard, especially some of the leadership and relational folks.

Incentivized