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Apache HBase is a NoSQL database.https://dudodiprj2sv7.cloudfront.net/product-logos/oa/Nx/3FDLWRE2Z8PE.pngNo SQL Database to Support Near Real Time AnalyticsHBase 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.,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.,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.,8,It supports the near real-time use cases when integrated with Spark Streaming. It helps to store huge volume of records with consistent reads/writes. Maintenance is the pain point as it requires some maintenance and monitoring of regional servers and nodes,MongoDB, MySQL and Teradata Database,Apache Hive, Apache Spark, Looker,7HBase, The Only Enterprise NoSQL ChoiceHBase 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.,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.,Not for small data Requires a cluster,10,It is affordable, so it saves money It scales, so it allows for storage of everything, saving valuable data It removes the need for expensive proprietary data stores It saves money by allowing for offload from expensive RDBMS and paid storage,MongoDB,Apache Hive, Apache Spark, TensorFlow,10HBaseHBase 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 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.,Multi-tenancy is still work in progress Usability and beginner friendliness It has a bad reputation of being complex,HBase was always known for being developer friendly, so to mitigate that, a project called Apache Phoenix was created to allow for a familiar SQL interface on top of HBase. Along with Apache Hive, HBase is now accessible by mere mortals. For fast retrieval you'd use Phoenix and for analytical workloads you'd use Hive with HBase underneath. Having an open source nature, allows for wonderful contributions from a huge community.,10,We were able to scale our application from 5TB running in a relational database to 20TB on top of HBase Application availability was always high even with half of the nodes having hardware issues HBase can be used with standard mechanical harddrive storage. There's no need for fancy SAN or NAS storage with HBase which is almost always expensive.,Cassandra and MongoDB,10HBase - good for UI performance from a Hadoop clusterHBase 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.,Very fast query capability Resilient: by leveraging hdfs, hbase can handle server failure pretty well,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.,I like using Apache Phoenix to simplify JDBC access. Without Phoenix, hbase feels a bit inaccessible for folks mostly familiar with SQL.,7,Facilitates building of UI tools that provide valuable business insights,Presto, Apache Hive and Apache Drill,5Support for HBaseIt 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.,Good write throughput Good horizontal scalability Easy to operate on,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.,7,Easy to understand the underlying data model and find engineers to leverage and operate it. Easy to look up related issues and corresponding solutions to handle those issues.,7
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HBase
28 Ratings
Score 8.1 out of 101
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HBase Reviews

HBase
28 Ratings
Score 8.1 out of 101
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Vinaybabu Raghunandha Naidu profile photo
April 19, 2018

HBase Review: "No SQL Database to Support Near Real Time Analytics"

Score 8 out of 10
Vetted Review
Verified User
Review Source
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.
  • 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.
  • 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.
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.
Read Vinaybabu Raghunandha Naidu's full review
Timothy Spann profile photo
April 06, 2018

Review: "HBase, The Only Enterprise NoSQL Choice"

Score 10 out of 10
Vetted Review
Reseller
Review Source
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.
  • 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.
  • Not for small data
  • Requires a cluster
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.
Read Timothy Spann's full review
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September 13, 2017

User Review: "HBase"

Score 10 out of 10
Vetted Review
Reseller
Review Source
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 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.
  • Multi-tenancy is still work in progress
  • Usability and beginner friendliness
  • It has a bad reputation of being complex
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.
Read this authenticated review
Zack Riesland profile photo
April 14, 2017

Review: "HBase - good for UI performance from a Hadoop cluster"

Score 7 out of 10
Vetted Review
Verified User
Review Source
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.
  • Very fast query capability
  • Resilient: by leveraging hdfs, hbase can handle server failure pretty well
  • 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.
When you need very fast query responsiveness from very large data sets
Read Zack Riesland's full review
Chen Jin profile photo
April 04, 2017

User Review: "Support for HBase"

Score 7 out of 10
Vetted Review
Verified User
Review Source
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.
  • Good write throughput
  • Good horizontal scalability
  • Easy to operate on
  • 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.
Not good for extremely low latency online application, in particular read heavy app.
Read Chen Jin's full review
Rekha Joshi profile photo
November 24, 2015

Review: "Apache HBase: Through the Looking Glass!"

Score 7 out of 10
Vetted Review
Verified User
Review Source
Apache HBase was used for mastering solutions, for creating master data sets and reconciling conflicting data coming to Apache Hadoop systems.
  • 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.
  • 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.
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?
Read Rekha Joshi's full review
No photo available
June 20, 2016

Review: "HBase - a scaleable, consistent data store"

Score 7 out of 10
Vetted Review
Verified User
Review Source
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.
  • Scalability
  • Strong consistency
  • SQL layer
  • Too many processes
  • Difficult to manage many clusters
HBase is a good choice if you're looking for a scaleable, strongly consistent data store that supports both OLTP and some OLAP as well.
Read this authenticated review

Feature Scorecard Summary

Performance (2)
9.0
Availability (2)
8.5
Concurrency (2)
9.0
Security (2)
8.0
Scalability (2)
8.0
Data model flexibility (2)
9.5
Deployment model flexibility (2)
9.5

About HBase

Apache HBase is a NoSQL database.
Categories:  NoSQL Databases

HBase Technical Details

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