Best Data Integration Tools for Apache Airflow

Data warehouse metadata and tools that connect to it can be captured. You can track the workloads that matter to you and retroactively analyze user engagement, cost, performance, and performance of data products. You have complete visibility into your data platform. This includes who is accessing your data and how it's being used. We'll be sharing the secrets of how data teams create and deliver data products in these interviews. We also discuss tech stacks, best practices, and other lessons learned. Intermix.io provides end-to-end visibility through an easy-to use SaaS dashboard. You can collaborate with your entire team to create custom reports and get all the information you need to understand your data platform, cloud data warehouse, and the tools that connect it. Intermix.io, a SaaS product, collects metadata from your cloud data warehouse without any coding. We don't need access to any data you have copied into your data warehouse.

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

Prophecy allows you to connect with many more people, including data analysts and visual ETL developers. To create your pipelines, all you have to do is click and type a few SQL expressions. You will be creating high-quality, readable code for Spark or Airflow by using the Low-Code Designer. This code is then committed to your Git. Prophecy provides a gem builder that allows you to quickly create and roll out your own Frameworks. Data Quality, Encryption and new Sources are just a few examples. Prophecy offers best practices and infrastructure as managed service - making your life and operations easier! Prophecy makes it easy to create workflows that are high-performance and scale out using the cloud.

Ascend provides data teams with a unified platform that allows them to ingest and transform their data and create and manage their analytics engineering and data engineering workloads. Ascend is supported by DataAware intelligence. Ascend works in the background to ensure data integrity and optimize data workloads, which can reduce maintenance time by up to 90%. Ascend's multilingual flex-code interface allows you to use SQL, Java, Scala, and Python interchangeably. Quickly view data lineage and data profiles, job logs, system health, system health, and other important workload metrics at a glance. Ascend provides native connections to a growing number of data sources using our Flex-Code data connectors.

The Stackable platform was built with flexibility and openness in mind. It offers a curated collection of open source data apps such as Apache Kafka Apache Druid Trino and Apache Spark. Stackable is different from other offerings that either push proprietary solutions or further vendor lock-in. All data apps are seamlessly integrated and can be added to or removed at any time. It runs anywhere, on-prem and in the cloud, based on Kubernetes. You only need stackablectl, a Kubernetes Cluster and stackablectl to run your stackable data platform. You will be able to work with your data within minutes. Configure your one line startup command here. Similar to kubectl stackablectl was designed to interface easily with the Stackable data Platform. Use the command-line utility to deploy and maintain stackable data apps in Kubernetes. You can create, delete and update components with stackablectl.

Meltano offers the most flexibility in deployment options. You control your data stack from beginning to end. Since years, a growing number of connectors has been in production. You can run workflows in isolated environments and execute end-to-end testing. You can also version control everything. Open source gives you the power and flexibility to create your ideal data stack. You can easily define your entire project in code and work confidently with your team. The Meltano CLI allows you to quickly create your project and make it easy to replicate data. Meltano was designed to be the most efficient way to run dbt and manage your transformations. Your entire data stack can be defined in your project. This makes it easy to deploy it to production.