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.
HBase as the brother of big data
An Amazing Experience
HBASE!!!
No SQL Database to Support Near Real Time Analytics
HBase, The Only Enterprise NoSQL Choice
HBase
HBase - good for UI performance from a Hadoop cluster
Support for HBase
HBase - a scaleable, consistent data store
Apache HBase: Through the Looking Glass!
Awards
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Popular Features
- Availability (5)7.878%
- Security (5)7.878%
- Performance (5)7.171%
- Concurrency (5)7.070%
Pricing
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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What is MarkLogic Server?
MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities. The vendor states it is the most secure multi-model database, and it’s deployable in any environment. They state it is an ideal database to power a data hub.
What is Couchbase Capella?
The Couchbase Capella product is a fully managed DBaaS automating setup and ongoing operations.
Product Demos
Apache Hbase Tutorial | Hadoop Hbase | Hbase Training | Intellipaat
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.
- 7.1Performance(5) Ratings
How fast the database performs under data load
- 7.8Availability(5) Ratings
Availability is the probability that the NoSQL database will be available to preform its function when called upon.
- 7Concurrency(5) Ratings
Concurrency is the ability for multiple processes to access or change shared data simultaneously. The greater the number of concurrent user processes that can execute without blocking each other, the greater the concurrency of the database system.
- 7.8Security(5) Ratings
Security features include authentication against external security mechanisms liker LDAP, Windows Active Directory, and authorization or privilege management. Some NoSQL databases also support encryption.
- 8.6Scalability(5) Ratings
NoSQL databases are inherently more stable than relational databases and have built-in support for replication and partitioning of data to support scalability.
- 7.1Data model flexibility(5) Ratings
NoSQL databases do not rely on rely on tables, columns, rows, or schemas to organize and retrieve data, but use use more flexible data models to accommodate the large volume and variety of data being generated by modern applications.
- 8.2Deployment model flexibility(5) Ratings
Can be deployed on-premise or in the cloud.
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What is HBase?
HBase Technical Details
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(32)Community Insights
- Business Problems Solved
- Recommendations
HBase has established itself as a crucial tool for various organizations, including PayPal, to store and retrieve records in near real time. Users have found that HBase excels in analytical use cases by providing faster lookup of records with consistent reads and writes, making it ideal for handling large datasets. It allows for faster querying of records compared to other NoSQL databases, resulting in improved data access and analysis capabilities. The ease of installation and configuration, thanks to its integration with the HDP Hortonworks stack, is another advantage that users appreciate.
One significant use case for HBase is as a data store for streaming data ingested through mechanisms like Apache NiFi, Apache Storm, Apache Spark Streaming, Apache Flink, and Streaming Analytics Manager. This allows organizations to efficiently manage and process continuous streams of data. Furthermore, HBase's ability to store structured, semi-structured, and unstructured data without requiring a pre-defined schema makes it a versatile choice for a range of applications.
Customers across industries have leveraged HBase successfully for their specific needs. In the retail sector, it serves as a datastore for product catalogs, session management systems, and revenue-generating platforms. Additionally, businesses involved in advertising and location analytics rely on HBase to generate locational information efficiently. Its scalability and read performance with avro data containing geospatial information make HBase preferable over alternatives like Cassandra.
HBase also plays a vital role in managing data within Apache Hadoop systems. It is used to create master data sets and reconcile conflicting data. Moreover, HBase serves as a secondary layer of storage that consolidates updates from upstream key-value stores.
While users highly recommend HBase for its data model consistency, scalability, and well-documented features, they do acknowledge the operational overhead associated with deploying and managing clusters. Nonetheless, this does not overshadow the significant benefits that organizations derive from using HBase to solve scalability and management issues related to multi-terabyte applications.
HBase is recommended for handling huge amounts of data and integrating with other tools. Users find HBase to be a good choice for scenarios requiring streaming ingest, fast lookups, and processing massive datasets. Its integration capabilities with other tools make it a valuable asset for organizations dealing with vast amounts of data.
HBase is also highly regarded for its real-time reporting capabilities over big data and seamless integration with business intelligence (BI) tools. Users recommend HBase as a reliable NoSQL datastore specifically designed to handle big data loads. It serves as an effective solution for storing unstructured or semi-structured data while providing easy integration with frontend applications.
Another common recommendation is to consider HBase's native integration with Hadoop and other data access engines. Users find HBase helpful for storing and processing non-relational data efficiently. Additionally, they recommend it as a reliable option for data storage and provision to other applications, making it suitable for various use cases.
It is important to evaluate HBase when considering NoSQL databases, as it offers unique benefits such as amazing structured/unstructured data storage capabilities and support for parallel programming. Users suggest utilizing HBase for specific use cases where large amounts of similar data need to be stored and accessed easily.
Lastly, users emphasize the importance of proper data modeling and workload tuning for successful implementation of HBase. They advise against using HBase for full table scan workloads and suggest considering relational databases when applicable. Additionally, they encourage the use of HBase for OLAP and OLTP use cases, highlighting its suitability for handling huge datasets and analytical processing needs.
Attribute Ratings
Reviews
(1-10 of 10)HBase as the brother of big data
An Amazing Experience
HBASE!!!
No SQL Database to Support Near Real Time Analytics
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
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.
HBase
HBase - good for UI performance from a Hadoop cluster
Support for HBase
HBase - a scaleable, consistent data store
Apache HBase: Through the Looking Glass!
- 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?