Data Lake Products – Explanation & Overivew

What are some data lake products?

A data lake is a storage system that can accommodate data of any size, type, or form – structured, semi-structured, and unstructured. Its unique flat architecture allows for quick on-demand retrieval of data for processing, analysis, and refinement.

Several powerful computing products take advantage of data lake capacity and speed:

Apache Hadoop Distributed File System (HDFS) is an open-source framework that allows for the storage and processing of large data sets by splitting files into large blocks and distributing them across nodes in a cluster.

Apache Hive is software that reads and writes big data stored[MOU1] in distributed databases and file systems. Its SQL-like interface and language, HiveQL, facilitates data summarization, query, and analysis. It is an open-source infrastructure built on top of Hadoop.

Google BigQuery is a RESTful web service used for cloud-based big data analytics. It supports data management, query, and access control of very large data sets. Like Apache Hive, it uses SQL-like syntax. It is a part of the Google Cloud Platform.

Amazon DynamoDB is a cloud-based NoSQL database service that supports both document and key-value store models. It supports applications that need consistent, single-digit millisecond latency.

SnapLogic’s Snaplex architecture connects cloud, on-premises, and big data endpoints across apps, databases, IoT, and APIs with SL eXtreme.

SnapLogic is the only unified data and application integration platform as a service (iPaaS) that can connect all your cloud, on-premises, and hybrid software applications and data sources.