Apache HBase vs. Cloudera Manager

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

It would be suited for customers who feel more comfortable with using a GUI. It is less appropriate for developers or engineers who are comfortable with command line

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

• Graphical user interface
• Management of third party applications start/stop/restart functionality through framework
• Support of Apache Hadoop ecosystem
• Ability to do "rolling restarts"

Incentivized

• 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

• Cloudera Manager needs to be more agile with integrating other applications, such as Accumulo 1.7, to their software.
• Cloudera Manager can do a better job at explaining why a node fails to add to a cluster using their assistant.
• Cloudera Manager should show graphs only when there is data, instead of showing just an empty box.

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

It is a well developed product with a good user interface.

Incentivized

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

I have not used any competitors, such as Hortonworks, because Cloudera Manager just works and meets all my customer's needs. I only have deployed Hadoop using command line, which is not easy to use and manage.

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 Manager has allowed our organization to deploy Apache Hadoop to operations quicker and with less training versus using the command line exclusively.
• Increased employee efficiency.
• Increased product adoption.

Incentivized