MemSQL, the leader in real-time and historical Big Data analytics, has introduced a new productivity tool - MemSQL Loader - that improves data ingest from popular data stores like Amazon Web Services S3 and the Hadoop Distributed File System (HDFS). The company said that the new data loading tool saves time and speeds data pipelines between popular data stores, including capability to perform direct streaming from the originating datastore in a single transfer while supporting multiple parallel input streams.
The MemSQL Loader is also available as open source, providing developers the ability to adapt it to their favorite data source. In addition, the MemSQL Loader supports automatic loading of batches of files or objects, automates loading processes and enables queuing of jobs to further simplify ingestion of data.
Nikita Shamgunov, Chief Technology Officer and co-founder, MemSQL
The MemSQL Loader is another innovation of simplifying MemSQL implementations with production data workflows. After working with customers during their MemSQL deployments, we found a simple way to eliminate steps in data pipelines, saving them time and reducing complexity. By streaming directly from popular data stores like Amazon S3 and HDFS, we offer customers an easy way to get started, and an efficient way to integrate the real-time transactions and analytics of MemSQL into existing environments.
