Is HBase good for time series?

Is HBase good for time series?

Time-series applications (sensor data, application/system logging events, user interactions etc) present a new set of data storage challenges: very high velocity and very high volume of data. This talk will present the recent development in Apache HBase that make it a good fit for time-series applications.

Is HBase a time series database?

It utilizes a real time map-reduce architecture for aggregations using Hbase coprocessors. However, as Pinterest grew and the number of reports grew, as well as the usage and volume of data within the reports, it exposed several scalability challenges.

What is HBase not good for?

When to use HBase HBase is not optimized for classic transactional applications or even relational analytics. If you find that your data is stored in collections, for example some meta data, message data or binary data that is all keyed on the same value, then you should consider HBase.

Is HBase real time?

Unlike Hive, HBase operations run in real-time on its database rather than MapReduce jobs. So, you have random access capabilities — something that’s missing from HDFS.

What are the disadvantages to HBase?

Limitations with HBase: HBase cannot perform functions like SQL. It doesn’t support SQL structure, so it does not contain any query optimizer. HBase is CPU and Memory intensive with large sequential input or output access while as Map Reduce jobs are primarily input or output bound with fixed memory.

What are the advantages and disadvantages of HBase?

HBase pros and cons

  • Great for analytics in association with Hadoop MapReduce.
  • It can handle very large volumes of data.
  • Supports scaling out in coordination with Hadoop file system even on commodity hardware.
  • Fault tolerance.
  • License free.
  • Very flexible on schema design/no fixed schema.

Is HBase OLAP or OLTP?

Apache Hive is mainly used for batch processing i.e. OLAP but HBase is extensively used for transactional processing wherein the response time of the query is not highly interactive i.e. OLTP. Unlike Hive, operations in HBase are run in real-time on the database instead of transforming into mapreduce jobs.

Do people still use HBase?

We have data on 12,922 companies that use Apache Hbase. The companies using Apache Hbase are most often found in United States and in the Computer Software industry. Apache Hbase is most often used by companies with 50-200 employees and 1M-10M dollars in revenue.

What are the advantages of HBase?

Advantages of HBase

  • Random and consistent Reads/Writes access in high volume request.
  • Auto failover and reliability.
  • Flexible, column-based multidimensional map structure.
  • Variable Schema: columns can be added and removed dynamically.
  • Integration with Java client, Thrift and REST APIs.
  • MapReduce and Hive/Pig integration.

What is the major advantage of using HBase?

Advantages of HBase Can store large data sets on top of HDFS file storage and will aggregate and analyze billions of rows present in the HBase tables. In HBase, the database can be shared. Operations such as data reading and processing will take small amount of time as compared to traditional relational models.

Can HBase be used for OLTP?

HBase is a database built on top of the Hadoop file system. It provides row-level read and write access and is optimized for high throughput OLTP-type workloads.

Is HBase good for OLAP?