Apache HBase vs. Cloudera Enterprise Data Hub

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.

Incentivized

Cloudera excels at seamless migrations and upgrades.



Cloudera supports self-healing and data center
replacement of failed cloud instances while maintaining the state.



Cloudera is essential to increase or decrease
capacity through the user interface or API.



Cloudera is great at simplifying big data analytics
by providing the technology and tools needed to gain insights from IoT and
connected devices to help monitor and condition our assets.



Cloudera's cybersecurity platform option offers
stronger anomaly detection, visibility, and prevention, as well as faster
behavioral analysis.



Cloudera is beneficial for enabling and utilizing
the platform's machine learning and ad-hoc queries while securely storing,
retrieving, and analyzing any volume of data at scale.

Incentivized

• 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.

Incentivized

• Excellent management capabilities via Cloudera Manager.
• Open source and does not restrict our data to be bound by a proprietary format.
• Offers excellent support for data governance and auditing.
• Has all the components that would help us build a data hub.
• Excellent platform support offered by Cloudera.

• 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.

Incentivized

• Not fully Open Source, couple of components of the distributions are privately owned, meaning with public contributions are not welcome
• Improvements to Cloudera manager can only be recommended. its very hard to get it done once recommended as the full control is with them.
• Should make components more aligned to Open Source rather than making it closed sourced.
• Custom Features of open source software tools supported only by Cloudera are tricky. Cant commit changes to tools like Hue.
• Improvements to Cluster Management tool is required, which are already available to its competitors.

Incentivized

There's really not anything else out there that I've seen comparable for my use cases. HBase has never proven me wrong. Some companies align their whole business on HBase and are moving all of their infrastructure from other database engines to HBase. It's also open source and has a very collaborative community.

Incentivized

Likely to renew the use in case the requirements for Cloudera remain valid. The rapid change in customer requirements and solutions that must be validated, integrated or tested changes. As the maturity of the solution increases, the requirements to renew use decrease. From a solution feature perspective by itself would probably grade 10.

Cassandra os great for writes. But with large datasets, depending, not as great as HBASE. Cassandra does support parquet now. HBase still performance issues. Cassandra has use cases of being used as time series. HBase, it fails miserably. GeoSpatial data, Hbase does work to an extent. HA between the two are almost the same.

Incentivized

Cloudera is
compatible with Windows operating systems, and Mac allows cloud-based
deployment, it is also very useful to configure data encryption, guarantee
protocols, and security policies. It also provides integrated auditing and
monitoring capabilities, as well as a control comprehensive data repository for
the enterprise, and ensures vendor compatibility through its open-source
architecture.

Incentivized

• As Hbase is a noSql database, here we don't have transaction support and we cannot do many operations on the data.
• Not having the feature of primary or a composite primary key is an issue as the architecture to be defined cannot be the same legacy type. Also the transaction concept is not applicable here.
• The way data is printed on console is not so user-friendly. So we had to use some abstraction over HBase (eg apache phoenix) which means there is one new component to handle.

Incentivized

• Cloudera products are the most widely. It is more business friendly as data is more secure. The sensitive data that you operate on is local to you and your project rather than processing this data on Cloud.
• Cloudera is definitely faster as wait time is reduced if on Cloud.
• A lot range of products are covered. So it is definitely good for businesses and had good returns on investments.