Fast Turnaround From Ingest to Insight

When you’re trying to glean wisdom from large troves of data, fast end-to-end turnaround time is a challenge because most data requires significant clean-up or format-munging before you can query it in a useful way. For teams that use a Hadoop cluster to perform data cleanup and transformation, significant time and effort is often spent moving large amounts of data between the Hadoop cluster and the database. To address this bottleneck, Aster Data provides the Aster-Hadoop Adapter, the fastest way to move data from Hadoop into Aster Database.

For example, a web analytics team can use Hadoop to perform the initial ETL processing that loads and cleans the data from its many web server logs and application logs. Once the data is cleaned, the Aster-Hadoop Adapter can seamlessly copy the resulting data into Aster Database, where analysts can write and run complex path-analysis queries in Aster Datbase’s familiar SQL environment with SQL-MapReduce® analytical functions.

Key Advantages of Aster-Hadoop Adapter

The Aster-Hadoop Adapter consists of SQL-MapReduce functions that provide ultra-fast, two-way data loading between Hadoop Distributed File System (HDFS) and Aster Database. The adapter has the following features:

Scalable: Built on Aster’s patented SQL-MapReduce framework, so the adapter scales with the size of your cluster and takes advantage of the distributed nature of your database tables in Aster.
Flexible: Deploying Aster Database and Hadoop together gives you the maximum flexibility in choosing your data clean-up tools: Use any combination of functions you have built in Hadoop, functions you have built in Aster Database, and off-the-shelf functions from Aster’s extensive SQL-MapReduce library.
Cost-effective: Enables you to use Hadoop for your initial ETL and data cleanup tasks, so you can cut your overall cost of handling big data.
Easy to use: An analyst invokes a simple SQL command in Aster Database to import the results of a Hadoop-MapReduce job, allowing deeper analysis of that data in Aster Database. The adapter automatically parallelizes the load operation, so no specialized Hadoop knowledge is required.
Familiar SQL syntax: Analysts use familiar SQL SELECT statements and distributed table structures to ensure that imported data is distributed evenly in the cluster, or to ensure that exported data is streamed in an even, parallel fashion to Hadoop.
Data Consistency: Aster Database’s data integrity and transactional consistency capabilities treat the data load operation as an SQL transaction, ensuring that the data load or export is always consistent and can be carried out while other queries are running in parallel in Aster Database.
Extensibility: Your analytics team can easily augment the adapter functions using SQL-MapReduce to provide further customization that suits your environment and workload.

Learn More

To learn more about the Aster-Hadoop Adapter, contact us by phone at 1.888.Aster.Data, or e-mail info@asterdata.com.