HBase

I use HBase because it is a NoSQL database and it is open sourced and can store big data. We can store any structured, semi-structured and unstructured data easily. One other major benefit is, it is a columnar database so no need to specify any schema. I generally use it when I store the streaming data, the analysis is also faster after connecting the HBase with Spark. HBase is a mature database so we can connect HBase with various execution engine and other component using JDBC.

HBase was used as a datastore for the retails product catalog and session maangement

HBase is used as part of the company's main revenue generating platform. We're using it store data with usages of mapreduce, generates locational information for advertising business and location analytics. Storage wise, it made sense to use HBASE over Cassandra, as well as for read performance with avro data with geospatial information in the data

HBase was used in my previous organization(PayPal) where we needed a database for storing and retrieving records in near real time. It was used within consumer analytics and other sub-teams. It supported our near real-time use analytical cases by proving a faster lookup of records with consistency reads/writes. Apart from that, helped in querying the records much faster than other NoSQL databases.

HBase is being used by multiple organizations and internally it is used company-wide. it solves a large range of problems and provides unique solutions when we need a NoSQL store.

HBase provides the best of breed solutions for any NoSQL storage needs. One of the main important features is it is part of the HDP Hortonworks stack so it is installed by default so there's nothing else to install or configure. It is easy to administer with Ambari and scales to any size I need. It runs on top of HDFS so my data is safe, secure and scalable.

I use it as a store for data that is ingested via various streaming mechanisms including Apache NiFi, Apache Storm, Apache Spark Streaming, Apache Flink and Streaming Analytics Manager. It provides an easy key-value type store with fast scans for data access. I also run Apache Phoenix on top to provide a fast clean SQL interface to all of my data.

HBase solves problems of scalability and management of multi-terabyte applications. It makes scaling to +1 nodes very easy, especially through Ambari. It is built with fault tolerance and availability in mind. You can use it on a single node but it shines on multi-node infrastructure. With high data access speed and resiliency, I wouldn't recommend any other NoSQL database for general use.

HBase makes it possible to provide sub-second UI responsiveness when querying very large data sets. This is in contrast to something like Hive, which could take many minutes.

It is used as a data store that consolidates the updates from the upstream key-value store where upstream store only stores the updates that meet the high qps and low latency. HBase is the secondary layer of the storage that consolidate all the updates for a given row key and serves as a upstream for hive table.

We use HBase as a secondary data store. We chose it mainly for its strongly consistent data model, and scalability. It has a pretty good documentation and a strong and active developer community that is still growing. The main downside is its many moving parts and operational overhead of deploying and managing clusters.

Apache HBase was used for mastering solutions, for creating master data sets and reconciling conflicting data coming to Apache Hadoop systems.