Meltano

cloud based open-source data integration alternative to sync data from any applications, APIs, and databases to data warehouses, data lakes, and other destinations.
The company recently raised $5.2 Million in seed funding round.

• On another end, you have a target, usually named in target-something format , contemplate it as a target (very logical, isn’t it?).
• All plans have 24/7 global support, and Professional and Enterprise plans have additional onboarding and personalized attention.
• And Meltano’s reliance on Singer offers big advantages, but the serious downside is that connectors can break and leave your computer data stranded.
• Looking for insights to come together and collaborate within the context of a single version-controlled Meltano project.

Segment includes 300+ connectors built-in, which can be found across all plans.
Segment offers several customer-focused features you won’t find with Meltano , including merging personas, dividing by stages in the client journey, and more.

Businesses searching for an all-in-one platform with SQL-based connectivity.
Precog takes a very different method of ETL connectors than its competitors.
Companies with low data volumes or large budgets searching for an industry-leading ELT tool.

Section: Enterprise-grade Platform Without The Cost And Hassle

A common use case would be to manage ELT pipelines with Meltano and as part of ensuring the standard of the data in those pipelines, teams generate Great Expectations.
With a data integration platform, you can actually create and maintain the various pipelines your computer data stack requires.

• Integrating everything with Matillion’s ecosystem can streamline support.
• It spun off from its parent company in 2021 and contains since raised $12.4 million in funding.
• Estuary Flow Platform is really a real-time data integration solution designed for the future.
• It supports a lot more than 250 data sources and creates custom integrations upon request, which are maintained by the Portable team.

This goes a long way toward building a reliable data platform that reflects the true state of your business’s data.
Meltano emerged from GitLab being an ELT platform which has evolved into a full-blown DataOps platform infrastructure.
The business has announced version 2.0 of the platform which comes with a load of new features.

Airbyte Pricing

At some time, data should be transformed from the foundation format into one that’s usable at the destination.
Pre-built connectors will be the primary solution to differentiate ETL / ELT solutions, because they enable data teams to focus only on the insights to create.
The Rivery Custom API feature lets you connect to data sources without built-in integrations.
Also you can request custom data sources from the Rivery team.

Currently, you can self-host Meltano (typically, on-prem) and work with a Git repository as a backup.
Airbyte also offers a Slack and Discourse community where help can be acquired from the Airbyte team, other users or contributors.
Engineering analytics Higher efficiency & impactFinance & Ops analytics Automated projections and insights.
Stitch provides chat and email support to all customers during normal business hours.

Yes; paid cloud-hosted and enterprise tiers are also available.
Before we dive deeper right into a few specifics, here is a comparison table highlighting the key differences in every three platforms.
Real-time data architecture is known as challenging for some engineers.

Another half is ensuring their technical specifications line up together with your requirements.
Let’s approach the nuances of the three platforms by comparing them head-on.
Founded in New York by data industry veterans, Estuary is really a relatively new company that is growing rapidly.
Flow combines the simple popular ELT tools with the scalability and efficiency of data streaming.

In reality, the complex nature of your data infrastructure might make it necessary to customize — whether that means adding a new connector or crafting a highly specific pipeline.
Extract, Transform, Load) are the two most elementary sequences a pipeline might have.
Ultimately, all data pipelines must extract data from the source and load it to a destination.