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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 Enterprises (1,001+ employees).
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Comparisons

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Reviews From Top Reviewers

View all reviews
(1-5 of 10)

Apache HBase: Through the Looking Glass!

Rating: 7 out of 10
Incentivized
November 25, 2015
RJ
Rekha Joshi
Staff Software Engineer
Intuit (Computer Software, 5001-10,000 employees)
Vetted Review
Verified User
Apache HBase
2 years of experience
View profile
Use Cases and Deployment Scope
Apache HBase was used for mastering solutions, for creating master data sets and reconciling conflicting data coming to Apache Hadoop systems.
Pros
  • Apache HBase is a widely used java based distributed NoSQL environment on Apache Hadoop.
  • While there has been growing interest and efforts in in memory computing, there are investments on Apache Hadoop (or hadoop provider variants) across domains. So that is a large market.
  • I worked on HBase for applications which needed to provide strong consistency and interact with Apache Hadoop.
Cons
  • You could encounter issues like region is not online or NotServingException or region server going down, out of memory errors.
  • As HBase works with Zookeeper, care needs to be taken it is correctly set up. Most issues pertain usually to environment setup, configuration, shared load on system or maintenance.
  • The performance across workloads when evaluated against other NoSQL variants was not best in class, this is most times okay, but can be improved.
  • If you use Apache HBase, and want to upgrade it for some features then you might need to do a compatibility check against your Apache Hadoop and Apache HBase versions, there are dependency to think about.
  • The HBase master slave becomes the single point of failure, and may not be a preferred design.It is not highly available system.
  • Last I checked it did not have well tested easy integrations with Spark, and that can help.
Likelihood to Recommend
The key questions I ask when choosing NoSQL distributed database:

  • What is the application's inherent need? Does this component fit well in the design?
  • Does it provide high data security?
  • How does it assure there is no data loss?
  • How can I make sure it is a highly available system, and no downtime for customer?
  • Does it give me the best linear scalability?
  • What kind of tuning parameters does it allow the user to configure?
  • How does it stack up against other NoSQL variants on features, scalability, ease of use/contribute to and maturity of product?
  • What throughput can it attain under different kinds of workloads?

HBASE!!!

Rating: 8 out of 10
Incentivized
December 13, 2018
AA
Anson Abraham
Data Lord
Envisagenics, Inc. (Marketing and Advertising, 51-200 employees)
Vetted Review
Verified User
Apache HBase
5 years of experience
View profile
Use Cases and Deployment Scope
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
Pros
  • Excellent for read performance
  • Great store of file format of avro
  • Easy integration into mapreduce
  • Replication ability
Cons
  • 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
Likelihood to Recommend
It does depend on the use case scenario. It works really well if your schema doesn't really need relational features. It's really good for that. If you want to run as transactional, not a good idea. Relational analytics is not good for this, as well as edge network data. If you're using PB of data, then HBASE is best suited in this case as well.

HBase as the brother of big data

Rating: 7 out of 10
Incentivized
March 16, 2019
RM
RAVI MISHRA
Data Engineer
ElogicSquare Analytics Pvt. Limited, Clearsense (Information Technology and Services, 11-50 employees)
Vetted Review
Verified User
Apache HBase
3 years of experience
View profile
Use Cases and Deployment Scope
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.
Pros
  • HBase stores the big data in a great manner and it is horizontally scalable.
  • Another major reason is security, we can secure the HBase database using Atlas, Ranger.
  • Store any format of data like structured, semi-structured and unstructured.
  • Consistency
  • Strongly consistent reads and writes are provided by HBase, we use it for high-speed requirements if we do not need RDBMS-supported features such as full transaction support or typed columns.
Cons
  • There are very few commands in HBase.
  • Stored procedures functionality is not available so it should be implemented.
  • 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. HBase integrated with Map-reduce jobs will result in random latencies.
Likelihood to Recommend
While we have a variable schema with slightly different rows and when you are going for a key dependent access to our stored data, we prefer to use HBase. No requirement of relational features. If we do not need features like transaction, triggers, complex query, complex joins etc. then go for HBase.

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

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.
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