Apache Kudu Reviews & Product Details

1. Implementing Lambda Architecture (Both Batch & Real Time Streaming) with Kudu is quite straightforward. We additionally used Streamsets as the Ingestion Platform which has quite a good coupling with Kudu.

2. Makes Real Time Analytics Quite Straightforward. We used Kudu to run multiple Real Time Campaigns.

3. Tailor Made for Implementing Data Warehouses within a Big Data Environment.

4. Nice Upsert Functionality. Review collected by and hosted on G2.com.

1. Partition Limitation - Is limited to 2000 tablets/tablet server.

2. Faces Random Timeouts while approaching the tablet number limitation (max 2000/server).

3. Needs a Conformed Schema. No automatic handling of drifting schemas.

4. Needs a Primary Key for every table.

5. #3 & #4 are not really cons per se. Review collected by and hosted on G2.com.

To my mind, what I found most helpful about Apache Kudu is the possibility to make quite complex data aggregations through SQL engines while also being able to efficiently perform updates Review collected by and hosted on G2.com.

Probably two downsides of Apache Kudu to take into account are partitioning configuration, as it's quite hard to find the best partitioning set up for the particular use case performance, and also the fact that Kudu does not balance charge if a new node is added to the cluster. Review collected by and hosted on G2.com.

Its quite good while reading and loading and best columnar database on top of hadoop. This kudu come with Cloudera so all component in one place. integration with impala script and compatible with parquet file format make it make more dynamic. Its dynamic partition also help during debugging. Kudu hive metastore integration is also make hive and kudu table accessible from same platform. The incremental data is replicated without any issue for end users. It support almost all ANSI sql so look very familiar. Review collected by and hosted on G2.com.

Kudu partitioning is done only on primary key which is not always suitable. Some cases we have time stamp as partition key but could not be primary key so reading huge table is concern here. So this need to be change in future . There is concern over Kudu Context concern with impala integration. Currently JDBC connectivity has still some issue for huge data. Its camecase table name issue.Kudu tables with a column name containing upper case or non-ascii characters may not be used as an external table in Impala. Columns may be renamed in Kudu to work around this issue. Review collected by and hosted on G2.com.

Speed of execution, especially in comparison to Apache Hive. Flexibility to work as a regular RDBMS table. It can be used for huge datamarts with CDC logic at ease. Review collected by and hosted on G2.com.

You have to decide the primary key for each and every object. So, more focus on the Data Modelling aspect. Review collected by and hosted on G2.com.

Easily accessible from APACHE Impala query engine, so building dashboard and OLAP experience is seamless. Review collected by and hosted on G2.com.

With a large number of streaming data, the load on the system increases exponentially, affecting other services running on the same server. Review collected by and hosted on G2.com.

Kudu-Impala Integration Features

Raft Consensus Algorithm use to guarantee fault tolerance Review collected by and hosted on G2.com.

Limited Scalability : data you can have in Kudu per cluster node and per cluster Review collected by and hosted on G2.com.

The best benefit is that you can run analytics on top of Hadoop. You don't need to propose an alternative big data solution to customer to run analytics if they have already selected Hadoop for Big Data storage. Review collected by and hosted on G2.com.

Kudu has limitations in the type of data it can handle. You can't store complex structured data as you can do with Impala. Review collected by and hosted on G2.com.

Easy to use

Updation and deletion which is not available in hive tables

Fast insertion deletion all ACID operations Review collected by and hosted on G2.com.

Documentations are not available specially detailing heavy workloads, optimizations Review collected by and hosted on G2.com.

no need to learn HBase for Real-Time processing, Apache Kudu can help you. easy to learn, efficient and you can update the records. it provides Review collected by and hosted on G2.com.

Primary must be the first column, some time it is difficult to maintain 1st column as the primary key. Review collected by and hosted on G2.com.

the query is very fast and has a great performance. Review collected by and hosted on G2.com.

it consume a lot of memory which destroy the system in long time. Review collected by and hosted on G2.com.