As more enterprises move to incorporate Hadoop-based data lakes as part of a Big Data strategy, data architects are seeking Apache Sqoop alternatives that can ingest data into a Hadoop solution more quickly and easily.

As a free, open source solution, Apache Sqoop is often the initial choice for data administrators looking for a way to capture, load, store and manage a Hadoop data lake. And while Sqoop is still a great solution for enterprises that are just beginning to explore the potential of data lake, Apache Sqoop alternatives like Qlik (Attunity) offer a more powerful approach to meet the requirements of the modern enterprise.

Qlik (Attunity): one of the leading Apache Sqoop alternatives

Qlik (Attunity) provides a universal data replication and data ingestion solution that moves data easily, securely and efficiently with minimal impact on operations. With Qlik (Attunity), enterprises can replicate, synchronize, distribute, consolidate and ingest data across all major databases, data warehouses and Hadoop, on premises and in the cloud.

As one of the most effective Apache Sqoop alternatives, Qlik (Attunity) provides an easy and scalable data ingest platform that delivers data efficiently while ensuring high performance to different types of data lakes.

Comparing Qlik (Attunity) to other Apache Sqoop alternatives

Qlik (Attunity) outperforms Sqoop and other Apache Sqoop alternatives by providing:

• Greater simplicity - administrators can use an intuitive and configurable graphical user interface to set up data feeds with no manual coding.
• Scalability – with Qlik (Attunity), enterprises can scale to ingest data from hundreds and thousands of databases, managing data ingestion with centralized monitoring capabilities.
• Support for multiple source systems – as one of the most popular Apache Sqoop alternatives, Qlik (Attunity) provides a single platform that supports many types of sources including data warehouses, mainframe systems at all major RDBMS.
• High performance with low risk – Qlik (Attunity) offers optimized and certified integration into all Hadoop distributions, including Cloudera, Hortonworks, MapR, as well as Kafka and Cloud platforms.
• Database CDC technology that ensures the highest possible performance by incrementally ingesting data sets continuously and efficiently while delivering data immediately, with near linear scalability and virtually zero latency.