Best Data Integration Tools for Outreach

Find and compare the best Data Integration tools for Outreach in 2024

Use the comparison tool below to compare the top Data Integration tools for Outreach on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Dataddo Reviews

    Dataddo

    Dataddo

    $35/source/month
    Dataddo is a fully-managed, no-code data integration platform that connects cloud-based applications and dashboarding tools, data warehouses, and other data storages. Dataddo offers three main products: - Data to Dashboards, which lets users send data from online sources straight to dashboarding apps like Tableau, Power BI, and Google Data Studio for insights in record time. A free version is available for this product! - Data Anywhere, which enables users to send data from any A to any B—from apps to warehouses or dashboards (ETL, end to end), between warehouses (ETL), and from warehouses back into apps (reverse ETL). - Headless Data Integration, which allows enterprises to build their own data products on top of the unified Dataddo API and get all integrations in one. The company’s engineers manage all API changes, proactively monitor and fix pipelines, and build new connectors free of charge in around 10 business days. The platform is SOC 2 Type II certified and compliant with all major data privacy laws around the globe, including ISO 27001. From the first log-in to complete, automated pipelines, get your data flowing from sources to destinations in just a few clicks.
  • 2
    Peaka Reviews

    Peaka

    Peaka

    $1 per month
    Integrate your data sources including relational and NoSQL database, SaaS and APIs. You can query them immediately as a single source of data. Process data wherever you are. Data from different sources can be merged, retrieved, and cached. Use webhooks for streaming data from Kafka or Segment into the Peaka Table. Real-time data access replaces nightly batch ingestion. Treat each data source as a relational database. Convert any API into a table and combine and join it with other data sources. Use familiar SQL to run queries on NoSQL databases. The same skills can be used to retrieve data from SQL and NoSQL database. You can query and filter your consolidated datasets to create new data sets. Use APIs to expose them and serve other apps or systems. Don't get bogged down with scripts and logs when setting up your data stack. Eliminate the burdens of managing and maintaining ETL pipelines.
  • 3
    Census Reviews
    Census is an operational analytics platform that syncs all your favorite apps with your data warehouse. Keep customer data in sync to bring together your customer success, sales and marketing teams. No engineering favors required. Census publishes SQL and dbt models automatically from your warehouse without you having to write a single line of code. Stop worrying about maintaining custom scripts or deciphering external APIs. Instead, focus on the business results. When everything is in your warehouse, you don't need "yet other source of truth". Census works on top your existing infrastructure. Pick a destination app and map the data. Voila! You shouldn't keep your data in quarterly reports. Every employee in your company can take action with Census. Live metrics in every app mean better business operations which results in happier users and more revenue.
  • 4
    Meltano Reviews
    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.
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