HBase Pros and Cons | Problems with HBase
1. HBase Pros and Cons
In our last HBase tutorial, we discussed HBase architecture. Today, we will discuss the disadvantages & advantages of HBase. It offers many other benefits that are not there in RDBMS but also some disadvantages and problems which make its use minimum. So, in this article, we will learn all HBase Pros and Cons with its Problems.
so, let’s start HBase Pros and Cons.
2. Pros of HBase
Here, we are listing all Advantages of HBase:
- Large data sets
HBase can handle as well as stores large datasets on top of HDFS file storage. Moreover, it aggregates and analyzes billions of rows present in the HBase tables.
- Databases breakdown
There is a time when relational databases breakdown, then HBase shine in the picture.
- Fast processing
As compared to traditional dataBase, data reading and processing in HBase will take the small amount of time.
- Failover support and load sharing
HBase is automatically recovered because HDFS is internally distributed and automatically recovered and HBase runs on top of HDFS. Also, we have this failover facility, using RegionServer replication.
Scalability is supported in both linear and modular form, in HBase.
There is no concept of fixed columns schema in HBase because it is schema-less. Hence, it defines only column families.
- Easy to use Java API for client access
Moreover, for programmatic access, HBase offers easy usage Java API.
For high-speed requirements, we can use it since it offers consistent reads and writes.
If these professionals can make a switch to Big Data, so can you:
3. Cons of HBase
Here, we are listing all limitations of HBase:
- Single point of failure
At the time when only one HMaster is used, there is a possibility of failure.
- No transaction support
In HBase, there is no support for the transaction.
- No handling of JOINS in database
Instead of the database itself, JOINs are handled in MapReduce layer.
- Sorted only on key
As RDBMS can be indexed on some arbitrary field, HBase is indexed and sorted only on key.
- Built-in authentication
There is no permissions or built-in authentication.
- Not a perfect replacement
Since HBase does not support some of the traditional model’s features, we cannot expect completely to use HBase as a replacement for traditional models.
- No support SQL structure
As there is no support for SQL structure, it cannot contain any query optimizer.
- Unpredictable latencies
While we integrate HBase with Map-reduce jobs, it will result in unpredictable latencies.
- Memory issues on the cluster
4. Problems with HBase
Apart from HBase Pros and Cons, there are some issues, such as:
- It is not possible to implement any cross data operations and joining operations, in HBase.
- When we want to migrate data from RDBMS external sources to HBase servers, HBase would require a new design.
- HBase is really tough for querying.
To access the data from HBase, there are slow improvements in the security for the different users.
- There is no support for partial keys completely in HBase.
- It permits only one default sort per table.
- To store the large size of binary files in HBase is very difficult.
- HBase’s storage will limit real-time queries as well as sorting.
- In HBase, default indexing is not present. That means, to perform indexing functionality in HBase, programmers have to define several lines of code or script.
- In terms of Hardware requirements and memory blocks allocations, it is expensive, such as:
- For distributed cluster environments, it is important that more servers should be installed.
- Also, it requires high memory machines, performance wise.
- It also has higher costing and maintenance.
So, this was all about HBase Pros and Cons. Hope you like this.
5. Conclusion: Pros and Cons of HBase
Hence, we have seen the best features which make HBase so popular. Moreover, we discussed major HBase pros and cons with its problem. However, to learn more about HBase, Keep visiting Dataflair.
Related article – HBase use cases and applications