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HBase

HBase

Overview

What is HBase?

The Apache HBase project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable.

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Learn from top reviewers

HBase as the brother of big data

Rating: 7 out of 10
March 16, 2019
IncentivizedVetted ReviewVerified User
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 ...
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RAVI MISHRA
Engineer - Information Technology
Data Engineer
ElogicSquare Analytics Pvt. Limited, Clearsense
Apache HBase3 years of experience

An Amazing Experience

Rating: 9 out of 10
December 14, 2018
IncentivizedVetted ReviewVerified User
HBase was used as a datastore for the retails product catalog and session maangement
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Bharadwaj (Brad) Chivukula
Manager - Information Technology
Director Of Engineering/Head of Reliability Engineering
Invitae
Apache HBase7 years of experience

HBASE!!!

Rating: 8 out of 10
December 13, 2018
IncentivizedVetted ReviewVerified User
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 b...
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Anson Abraham
Engineer - Engineering
Data Lord
Envisagenics, Inc.
Apache HBase5 years of experience

No SQL Database to Support Near Real Time Analytics

Rating: 8 out of 10
April 19, 2018
IncentivizedVetted ReviewVerified User
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 o...
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Vinaybabu Raghunandha Naidu
Engineer - Engineering
Software Engineer - Big Data Platform
Wish - Shopping Made Fun!
Apache HBase1 year of experience

HBase, The Only Enterprise NoSQL Choice

Rating: 10 out of 10
April 6, 2018
IncentivizedVetted Review
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 st...
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Timothy Spann
Engineer - Sales
Senior Solutions Engineer
Hortonworks
Apache HBase4 years of experience
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Pricing

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HBase

HBase

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What is HBase?

The Apache HBase project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable.

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  • No setup fee

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  • Premium Consulting/Integration Services

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Product Demos

Apache Hbase Tutorial | Hadoop Hbase | Hbase Training | Intellipaat

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Features

NoSQL Databases

NoSQL databases are designed to be used across large distrusted systems. They are notably much more scalable and much faster and handling very large data loads than traditional relational databases.

7.7
Avg 8.8
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Product Details

What is HBase?

HBase Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

The Apache HBase project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable.

Reviewers rate Scalability highest, with a score of 8.6.

The most common users of HBase are from Mid-sized Companies (51-1,000 employees).
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Comparisons

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Reviews From Top Reviewers

View all reviews
(1-5 of 7)

No SQL Database to Support Near Real Time Analytics

Rating: 8 out of 10
Incentivized
April 19, 2018
Use Cases and Deployment Scope
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.
Pros
  • Faster lookup of records using the row keys. It helped to fetch thousands of records in a much faster way using the row keys
  • As it is a columnar data store, helped us to improve the query performance and aggregations
  • Sharding helps us to optimize the data storage and retrieval. HBase provides automatic or manually sharding of tables.
  • Dynamic addition of columns and column family helped us to modify the schema with ease.
Cons
  • Identified issues with Hmaster when handling a huge number of nodes
  • Cannot have multiple indexes as row key is the only column which could be indexed.
  • HBase does not support partial row keys which limit its query performance.
Likelihood to Recommend
Hbase is well suited for large organizations with millions of operations performing on tables, real-time lookup of records in a table, range queries, random reads and writes and online analytics operations.

Hbase cannot be replaced for traditional databases as it cannot support all the features, CPU and memory intensive. Observed increased latency when using with MapReduce job joins.

HBase, The Only Enterprise NoSQL Choice

Rating: 10 out of 10
Incentivized
April 06, 2018
Use Cases and Deployment Scope
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.
Pros
  • Scalability. HBase can scale to trillions of records.
  • Fast. HBase is extremely fast to scan values or retrieve individual records by key.
  • HBase can be accessed by standard SQL via Apache Phoenix.
  • Integrated. I can easily store and retrieve data from HBase using Apache Spark.
  • It is easy to set up DR and backups.
  • Ingest. It is easy to ingest data into HBase via shell, Java, Apache NiFi, Storm, Spark, Flink, Python and other means.
Cons
  • Not for small data
  • Requires a cluster
Likelihood to Recommend
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.

Support for HBase

Rating: 7 out of 10
Incentivized
April 04, 2017
Use Cases and Deployment Scope
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.
Pros
  • Good write throughput
  • Good horizontal scalability
  • Easy to operate on
Cons
  • Better tool for investigating the key-value content for data validation.
  • Better tool for row key monitoring since our key contains timestamps.
  • Better tool for system-level metric monitoring.
Likelihood to Recommend
Not good for extremely low latency online application, in particular read heavy app.

HBase

Rating: 10 out of 10
Incentivized
September 13, 2017
Verified User
Engineer in Information Technology
Computer Software Company, 501-1000 employees
Vetted Review
Reseller
Apache HBase
3 years of experience
Use Cases and Deployment Scope
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.
Pros
  • HBase data access and retrieval only gets better with larger scale.
  • Fault tolerance is built in, if you have unreliable hardware, HBase will make every effort to keep your data online.
  • Extremely fast key lookups and write throughput.
Cons
  • Multi-tenancy is still work in progress
  • Usability and beginner friendliness
  • It has a bad reputation of being complex
Likelihood to Recommend
HBase typically fits well in low latency, tight SLA scenarios. It is not recommended to be used in situations where a relational database would fit better. So in essence, if you're trying to do a lot of analytical workloads or joins, HBase wouldn't fit so well. If primary key access is sufficient, then HBase is a good fit.

HBase - good for UI performance from a Hadoop cluster

Rating: 7 out of 10
Incentivized
April 14, 2017
ZR
Zack Riesland
Data Engineer / Software Engineer (Big Data - Cloud)
Sensus (Utilities, 1001-5000 employees)
Vetted Review
Verified User
Apache HBase
3 years of experience
View profile
Use Cases and Deployment Scope
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.
Pros
  • Very fast query capability
  • Resilient: by leveraging hdfs, hbase can handle server failure pretty well
Cons
  • Very schema dependent - you have to carefully choose your schema and key strategy in order to get good distribution and performance.
  • Over aggressive rebalancing - if you have to bounce your system - for example - hbase will spend quite a while trying to rebalance all the data as each server comes online.
Likelihood to Recommend
When you need very fast query responsiveness from very large data sets
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