HBase tables are ideal for QUERIES where normally you would use a KEY-value store. That is, where you retrieve a single row or a few rows, by testing a special unique key column using the = or IN operators.

HBase tables are not suitable for queries that produce large result sets with thousands of rows. HBase tables are also not suitable for queries that perform full table scans because the WHERE clause does not request specific values from the unique key column.

Use HBase tables for data that is inserted one row or a few rows at a time, such as by the INSERT ... VALUESsyntax. Loading data piecemeal like this into an HDFS-backed table produces many tiny files, which is a very inefficient layout for HDFS data files.

If the lack of an UPDATE statement in Impala is a problem for you, you can simulate single-row updates by doing an INSERT ... VALUES statement using an existing value for the key column. The old row value is hidden; only the new row value is seen by queries.

HBase tables are often wide (containing many columns) and sparse (with most column values NULL). For example, you might record hundreds of different data points for each user of an online service, such as whether the user had registered for an online game or ENABLED particular account features. With Impala and HBase, you could look up all the information for a specific customer efficiently in a single query. For any given customer, most of these columns might be NULL, because a typical customer might not make use of most features of an online service.

HBase tables are ideal for queries where normally you would use a key-value store. That is, where you retrieve a single row or a few rows, by testing a special unique key column using the = or IN operators.

HBase tables are not suitable for queries that produce large result sets with thousands of rows. HBase tables are also not suitable for queries that perform full table scans because the WHERE clause does not request specific values from the unique key column.

Use HBase tables for data that is inserted one row or a few rows at a time, such as by the INSERT ... VALUESsyntax. Loading data piecemeal like this into an HDFS-backed table produces many tiny files, which is a very inefficient layout for HDFS data files.

If the lack of an UPDATE statement in Impala is a problem for you, you can simulate single-row updates by doing an INSERT ... VALUES statement using an existing value for the key column. The old row value is hidden; only the new row value is seen by queries.

HBase tables are often wide (containing many columns) and sparse (with most column values NULL). For example, you might record hundreds of different data points for each user of an online service, such as whether the user had registered for an online game or enabled particular account features. With Impala and HBase, you could look up all the information for a specific customer efficiently in a single query. For any given customer, most of these columns might be NULL, because a typical customer might not make use of most features of an online service.