Apache HBase
Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. It is written in Java and provides fast random access to large amounts of structured data.
distributed
nonrelational
big-data
hadoop
Apache HBase: Open-Source Distributed Non-Relational Database
Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. It is written in Java and provides fast random access to large amounts of structured data.
What is Apache HBase?
Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. It is written in Java and runs on top of HDFS (Hadoop Distributed File System), providing Bigtable-like capabilities for Hadoop.
HBase provides fast random access to large amounts of structured data. It scales linearly to handle huge tables with billions of rows and millions of columns. HBase groups data together to store new data in a memory buffer and once the buffer fills up, it dumps the data to the disk. This provides faster read and write operations.
Some key features of HBase include:
- Linear and modular scalability
- Strict consistency reads and writes
- Automatic failover support between RegionServers
- Integration with Hadoop ecosystem (Pig, Hive, ZooKeeper, etc.)
- Easy to use Java API for client access
- MapReduce integration to utilize Hadoop's processing capabilities
- Query predicate push down via server side scan and get filters
- Thrift, REST and Avro APIs for client access
HBase is well suited for large datasets which need random, realtime read/write access such as stock market data, sensor data, electronic health record storage, recommendation system history or catalog lookup services.
Apache HBase Features
Features
- Distributed database
- Automatic sharding
- Strong consistency
- Fault tolerance
- Column-oriented store
- Integration with Hadoop ecosystem
Pricing
- Open Source
Pros
Scalability
High availability
Low latency
Flexible data model
Integration with MapReduce
Cons
Complex to operate
Steep learning curve
No secondary indexes
Limited query capabilities
Official Links
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