Trending ETL Tools in 2023
Until a decade ago, data teams used to circle around data silos, often trying to make sense of incomplete data, taking up a lot of man hours just trying to collect their data in a coherent format. The use of ETL tools now is rapidly altering this scenario by replacing cumbersome manual processes in most data engineering teams.
According to McKinsey & Co. report titled: The data-driven enterprise of 2025,
“By 2025, smart workflows and seamless interactions among humans and machines will likely be as standard as the corporate balance sheet, and most employees will use data to optimize nearly every aspect of their work.”
Therefore, having a single source of truth, a singular platform for all your data allows you to conserve scarce data engineering resources, which can then be deployed for vital business analytics.
What are ETL tools?
The entire process of aggregating data from multiple sources into a data warehouse/ data lake in a consistent standardized format is typically divided into three steps of ETL (Extract, Transform & Load). The first step in ETL involves extracting data from multiple sources like existing/legacy databases, SaaS applications, files and online docs. Which is followed by transforming the data to be loaded into a compatible format as per the data warehouse standards. Finally, the transformed data is loaded into a data warehouse.
Each one of these steps can (in theory) be done manually by composing bespoke scripts or doing a ridiculous number of mouse clicks. However, at any significant scale the process becomes horrendously complicated and dreary very fast. Thus, a data engineering team which starts out with benign intentions of business data analytics gets caught up in a malignant conflict with managing multiple data sources with ever changing APIs, protocols and custom requirements at all fronts.
To facilitate this entire ETL journey of data from multiple and disparate sources to the chosen data warehouse is where the ETL tools/platforms step in. These tools basically do all the heavy lifting of connecting to multiple data sources, keep track of dynamic API requirements, maintain and check the integrity of the data being moved and provide multiple options to transform the data. They also provide the options for choosing frequency of data transfer, types of inserts/upserts/updates required and create schemas for the incoming data sets. This provides tremendous advantages to the in-house data engineering teams who get access to all the data they need with ease, flexibility and scalability at their fingertips. Admittedly, their ability to provide advanced business analytics just takes off after that.
All your data at one place, structured according to specific business needs, helping drive impactful decisions. More productive and empowered data engineering teams.
Types of ETL tools
Enterprises today have the choice of picking an ETL tool that fits their data integration requirements. ETL tools can be segregated into 3 major types:
- Open-source ETL Tools: These tools are free to use, and data teams can customise them as per their requirements. Such platforms can support many integrations, but also call for a fairly high level of technical expertise. Also, there is little to no support available making them inappropriate for business-critical data warehouses. Talend and Airbyte are some popular open-source tools.
- On-premises ETL Tools: These tools need to be licensed by the enterprise and installed on one’s own infrastructure as a third-party service provider can’t host them. Oracle Data Integrator, IBM Infosphere Datastage and Dell Boomi are prominent examples in this category. They are usually very expensive and have specialized requirements.
- Cloud-first ETL Tools: Unlike on-premises tools, these tools can be hosted by a third-party service provider and can be easily accessed via a web browser. Additionally, cloud-first ETL tools do not require traditional software licensing and can be bought on a subscription basis. Companies like DataChannel, Fivetran, Stitch and Funnel enable a cloud-first approach to ETL.
How to evaluate ETL TOOLS?
When evaluating ETL tools, there are several factors to consider to determine their suitability for your organization's specific needs. Here are some key points to consider when evaluating DataChannel as an ETL tool:
- Ease of Use: ETL tool should have an intuitive interface that is easy to use, even for those without extensive technical knowledge. Its drag-and-drop interface simplifies the process of creating data integration workflows and allows you to easily map source and target data fields.
- Connectivity: Support for a wide range of data sources, including databases, cloud storage services, and APIs is a must for any ETL tool. This flexibility enables you to extract data from a variety of sources and transform it into a format that can be easily analyzed.
- Scalability: Any ETL tool should also be able to handle large volumes of data, making it suitable for enterprise-level data integration projects. It also supports parallel processing, which helps to speed up the data integration process.
- Data Transformation Capabilities: Your choice of ETL tool should also provide a wide range of data transformation functions, including filtering, and aggregation. These features enable you to clean and enrich your data before loading it into your target system.
- Granular Control Over Data: Granular control over data is an important feature of ETL (Extract, Transform, Load) tools that allow organizations to efficiently manage and integrate their data.
- Reverse ETL: ETL tools should also come with built-in reverse ETL capability to provide a two-way data flow, allowing businesses to write back data to source systems, synchronize data across various applications, and automate workflows. It further enhances efficiency and productivity by enabling data-driven decision-making and streamlining business processes.
Moving on, now let’s discuss about trending ETL tools being used widely in 2023:
As one of the very few data integration platforms that give you access to both ETL & reverse ETL capabilities, DataChannel is an automated no-code platform that creates stable data pipelines effortlessly. With 100+ pre-built data connectors, it gives you superb control over your data, supports all major cloud data warehouses while also offering a managed data warehousing capability. It has an intuitive interface which helps obtain full data visibility, ease of management and advanced scheduling features. DataChannel adheres to GDPR rules for data safety and provides integrations with Facebook Ads, Google Ads, Google Analytics 4, Amazon Seller Central, Shopify and almost all major SaaS platforms. It has in-built support for previewing data without leaving the platform and scheduling data transformation pipelines. DataChannel is known for its best in class support and on-boarding services. It is priced very competitively with a transparent pay-as-you-go model and offers a forever free tier.
Verdict: Versatile and value for money.
Rating on G2: 4.5/5
Fivetran is one of the leaders in the automated data integration space. A cloud based ETL platform that offers warehouse integrations with Snowflake, Azure & Redshift among other warehouse connections. Fivetran guarantees very high platform uptime and supports automated CDC replication, DBT transformations & cloud functions. It provides comprehensive privacy, security and compliance features for data security. It has class leading features for control over data access and detailed logging abilities. The platform is very expensive and can lead to significant costs very rapidly. The pricing model is also based on a complicated concept of consumption based on the number of monthly active rows (MAR) across all connectors and destinations. The support has been reported to be patchy and not suited for all customer needs. It does not support any reverse ETL capabilities.
Verdict: Powerful but very expensive and does not have built in reverse ETL.
Rating on G2: 4.2/5
Hevo supports various data integration connectors, ranging from cloud storage to SaaS apps. A cloud first ETL tool, it allows pre-load transformations and grants control over pipeline scheduling. It offers connections to relational databases PostgreSQL, MongoDB, and Google Sheets. With more than 15 destinations and the promise of zero maintenance, Hevo is committed to leveraging data for its clients to bridge the gap between data and insights with ease. They do not provide any managed data warehouse feature. The platform has been reported to provide frequent updates leading to disruptions in service. The pricing though competitive initially scales up very fast adding to costs.
Verdict: Competitive but expensive at scale.
Rating on G2: 4.3/ 5
Stitch has pre-built connectors for more than 100 data sources and has expertise in offering solutions for Sales, Marketing, and Product Intelligence. Stitch, was acquired by Talend in Nov 2018, provides quick fixes for data inconsistencies while also simplifying log analysis on the destination side. With its extensible ETL features, Stitch enables easy data analysis by making the use of tools such as Apache Spark, Google Data Studio, etc. Stitch has undergone a SOC2 security audit, offers ETL services that are HIPAA compliant, and complies with GDPR laws. It has a complicated user interface and non-intuitive flow. They have been slow to release new connectors with trending platforms and do not provide any managed data warehouse services. It provides open-source integration with the singer platform which enables anyone to develop new integration by utilizing Stitch infrastructure. However, these have been reported to be very tedious and poorly supported.
Verdict: Expensive, limited integrations and uncertain future pipeline.
Rating on G2: 4.5/5
A cloud based ETL tool primarily for marketing data that strives to deliver clean, accurate, and current data, Funnel can gather data from more than 500 different marketing data sources, including analytics, advertising, and CRM. Customers of Funnel benefit from both standard and bespoke rules, which can be used for everything from combining various traffic sources to changing undesirable campaign names. With its top-of-the-line data translation capabilities, Funnel also facilitates the reporting of marketing KPIs like ROAS, ROI, and CPC, among others. The tool is more marketing platform focussed and lacks extensive scheduling controls. It also does not provide any reverse ETL capabilities or managed data warehouse features.
Verdict: Expensive with limited capabilities.
Rating on G2: 4.5/5
One of the top open-source data integration platforms, Talend, is dedicated to democratizing data use. With its on-premises data integration platform, Talend streamlines ETL operations. Talend is committed to improving data quality in order to make it simpler for organizations to derive insights. It allows integration with well-known cloud service providers like Microsoft Azure & AWS and uses more than 100 connectors. The tool has limited memory capacity and cannot scale very well. It has very limited support and needs lots of tweaking for deployment. No scheduling feature and lack of any reverse ETL capabilities.
Verdict: Open source with restricted capabilities.
Rating on G2: 4.3/ 5
With real-time monitoring, newcomer Airbyte provides its clients with access to more than 140 connectors. Being an open-source ETL platform, it replicates data from applications, APIs & databases to data warehouses, lakes, and other destinations. Airbyte’s connectors accept both JSON scripts and normalized schema. There is no support available other than community which can lead to challenges in business-critical deployments. It has limited error handling and reporting capabilities. Has a very complicated pricing structure which has been estimated to be expensive. The tool suffers from scalability and has no reverse ETL features.
Verdict: Free tier with limited capabilities. Expensive at scale.
Rating on G2: 4.1/ 5
Organizations can either choose to go for paid or free Open-Source ETL tools. While paid tools usually have quality support, up-to-date documentation along with regular product updates to keep up with the changes in the databases and customer requirements. Free Open-Source tools allow businesses to customize the tool as per their requirements but require lots of technical effort. An ideal tool would be the one which gives quality support at a fair price and lots of customization features in a comprehensive package.
Can’t decide which tool is the best fit for your enterprise?
Set up a call with one of our sales expert or use our 14 day free trial to give it a try.
DataChannel – An integrated ETL & Reverse ETL solution
- 100+ Data Sources. DataChannel’s ever-expanding list of supported data sources includes all popular advertising, marketing, CRM, financial, and eCommerce platforms and apps along with support for ad-hoc files, google sheets, cloud storages, relational databases, and ingestion of real-time data using webhooks. If we do not have the integration you need, reach out to our team and we will build it for you for free.
- Powerful scheduling and orchestration features with granular control over scheduling down to the exact minute.
- Granular control over what data to move. Unlike most tools which are highly opinionated and dictate what data they would move, we allow you the ability to choose down to field level what data you need. If you need to add another dimension or metric down the line, our easy to use UI lets you do that in a single click without any breaking changes to your downstream process.
- Extensive Logging, fault tolerance and automated recovery allows for dependable and reliable pipelines. If we are unable to recover, the extensive notifications will alert you via slack, app and email for taking appropriate action.
- Built to scale at an affordable cost. Our best in class platform is built with all ETL best practices built to handle billions of rows of data and will scale with your business when you need them to, while allowing you to only pay for what you use today.
- Get started in minutes. Get started in minutes with our self-serve UI or with the help of our on-boarding experts who can guide you through the process. We provide extensive documentation support and content to guide you all the way.
- Managed Data Warehouse. While cloud data warehouses offer immense flexibility and opportunity, managing them can be a hassle without the right team and resources. If you do not want the trouble of managing them in-house, use our managed warehouse offering and get started today. Whenever you feel you are ready to do it in-house, simply configure your own warehouse and direct pipelines to it.
- Activate your data with Reverse ETL. Be future-ready and don’t let your data sit idle in the data warehouse or stay limited to your BI dashboards. The unidimensional approach toward data management is now undergoing a paradigm change. Instead, use DataChannel’s reverse ETL offering to send data to the tools your business teams use every day. Set up alerts & notifications on top of your data warehouse and sync customer data across all platforms converting your data warehouse into a powerful CDP (Customer Data Platform). You can even preview the data without ever leaving the platform.
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