11 Best ETL Tools for 2021

on Data Integration • January 9th, 2019 • Write for Hevo

Finding the ETL tool that fits your use case like a glove can be hard. This detailed guide aims to help you give a complete set of inputs in terms of broad classification, use cases, and an evaluation framework on the ETL tools in the market. The post also has a detailed comparison of these tools. All of this combined should assist you to pick the best ETL tool as per your use case. 

This is a fairly comprehensive blog. In case you are eager to just get to the point and discover the best cloud-based ETL tools, here is the list.

Top 11 ETL Tools Comparison

1. Hevo Data

  • Easy Setup and Highly Intuitive User InterfaceHevo has a minimal learning curve and can be set up in minutes. Once the user has quickly configured and connected both the data source and the destination warehouse, Hevo moves data in real-time
  • Fully Managed – No coding nor pipeline maintenance is required by your team
  • Unlimited Integrations – Hevo can provide connectivity to numerous cloud-based and on-site assets. Check out the complete list here.
  • Automatic Schema Mapping – Hevo automatically detects the schema of the incoming data and maps it to the destination schema. This feature frees you from the tedious job of manually configuring schema.
  • Effortless Data Transformations – Hevo provides a simple Python interface to clean, transform, and enrich any data before moving it to the warehouse. Read more on Hevo’s Transformations here. 

Sign up for a 14-day free trial here and experience efficient and effective ETL.

A snapshot of how to get started with Hevo is in the following video:

Hevo Data Pricing:

Hevo’s basic plan starts at $249/month. You can explore the detailed pricing here.

2. Informatica PowerCenter

Key Features of Informatica PowerCenter

  • Informatica PowerCenter provides an on-premise ETL tool that can integrate with a number of traditional database systems.
  • It is an enterprise-grade solution with comprehensive support for data governance, monitoring, master data management, and data masking.
  • It also has a cloud counterpart which allows accessing repositories deployed inside the organization’s premise and can execute transformation tasks in its cloud.
  • It is primarily batch-based ETL tool.
  • Informatica change connectors now support popular cloud data warehouses like AWS DynamoDB, AWS Redshift, etc. It also supports a variety of data storage solutions and software as a service offering. You can find a comprehensive list of connectors here.

Informatica PowerCenter Use case

Informatica power center is more suited for organizations that need enterprise-grade security and data governance within their on-premise data because of mandatory compliance requirements. Even the cloud version of Informatica Power Center is more suited for on-premise data and emphasis is on the data security part.

Informatica PowerCenter Pricing

Informatica Power center cloud starts from 2000$ per month for its most basic version. You can find the details of Informatica Pricing here. Pricing depends on parameters such as the data sources that you need to integrate with, security needed task flow orchestration requirement, and so on.

Informatica Power center pricing is not transparent and depends a lot on the contract negotiated by the customer and Informatica. AWS and Azure provide Informatica Power center on a pay as you go, pricing model.

3. IBM InfoSphere DataStage

Key Features of IBM InfoSphere DataStage

  • Like Powercenter, this is an enterprise product aimed at bigger organizations with legacy data systems.
  • Infosphere data stage has a cloud version that can be hosted in the IBM cloud, but here too the focus is on-premise databases and executing the transformation tasks in the cloud.
  • It is primarily batch-based.
  • IBM data stage has connectors to cloud-based data storage solutions like AWS S3 and Google cloud storage. Since it supports JDBC, software as a service data warehouses like Redshift which provides JDBC connectors can also be integrated. Support for connectors is not as comprehensive as Informatica Power center though.

IBM InfoSphere DataStage Use case

IBM Infosphere is suited for enterprise-grade applications that primarily run on on-premise databases.

IBM InfoSphere DataStage Pricing

Like in the case of Powercenter, on-premise pricing for the Infosphere is not transparent and is negotiated via contracts. Infosphere cloud pricing started from 6800$ per month for the smallest cloud deployment. Read more on the pricing here.

4. Talend

Key Features of Talend

  • Talend has a large suite of products ranging from data integration, big data management, to data preparation, and more.
  • Talend Data Fabric is a collection of all tools that come under the Talend Umbrella bundled with platinum customer support.
  • Talend Open Studio is open-source and can be used without paying if you do not use Talend Cloud.
  • Talend supports most cloud and on-premise databases and has connectors to software as a service offering as well.
  • Talend’s big bet is in the area of multi-cloud and hybrid cloud where customers with extremely high data protection requirements hedges themselves by using more than a cloud provider and on-premise systems.
  • Talend studio provides a UI to design the flow and transformation logic much like Infosphere and Power center.
  • Talend works on the basis of code generation approach and hence the code has to be built every time there is a change in logic.
  • Support for connectors is comprehensive like that of PowercenterCompared to PowerCenter and DataStage, Talend is a more recent tool in the same space.
  • Talend can operate both on-premise and on the cloud. It is mostly suited for batch processes.
  • Has a large suite of products ranging from data integration, big data management, to data preparation, and more. If you are looking for a tool that can get many of these tasks offloaded along with data integration, Talend might be suitable.

Talend Use case

Talend is an enterprise-grade solution with a strict emphasis on data governance and hybrid cloud architecture. If you are a financial institution or an enterprise with strict compliance requirements to spread risks across multiple clouds, then Talend can be a good option.

Talend also offers varied pricing, based on the set of products and features opted for. Talend data integration basic plan starts at $12,000/year. Read more about Talend pricing here.

5. Pentaho

Key Features of Pentaho

  • Also known as Kettle, Pentaho has an open-source community and an enterprise edition.
  • Like PowerCenter and DataStage, Pentaho is also built to cater to on-premise, batch ETL use cases.
  • It offers data integration and data processing features from a diverse set of data sources. 
  • Pentaho also bets heavily on the hybrid cloud and multi cloud-based architectures. 
  • Pentaho works on the basis of the interpretation of ETL procedures stored in XML format. Since there is no code generation involved, Pentaho is better than Talend in case of ad-hoc analysis.
  • Pentaho does not disclose pricing upfront.

Pentaho Use case

Pentaho is normally used when companies go for open source ETL tools in an on-premise ecosystem. Unlike the tools mentioned above, Pentaho does not focus on its own cloud. The full suite of Pentaho can be deployed in an on-premise or cloud provider. In that sense, it provides complete independence without being tied to any cloud provider.

Pentaho community edition is free to use. Pentaho enterprise edition price is not disclosed and is negotiated based on contracts. Talend also offers varied pricing, based on the set of products and features opted for. You can request for a quote here.

6. AWS Glue

Key Features of AWS Glue

  • Glue is a cloud-based real-time ETL tool provided by AWS on a pay as you model.
  • AWS glue is primarily batch-oriented, but can also support near real-time use cases based on lambda functions. 
  • If most of the data sources that you are looking to ingest data from are on AWS, Glue provides easy methods to ETL the data.
  • Support for sources and destinations outside the AWS ecosystem is not great
  • Glue has some noteworthy features – integrated data catalog, automatic schema discovery, and more. Read more about AWS Glue here.
  • AWS Glue combined with lambda functions allows it to implement a serverless full-fledged ETL pipeline.
  • AWS Glue has a pay-as-you-go pricing model. It charges an hourly rate, billed by the second. Read more about AWS Glue pricing here.

AWS Glue Use case

AWS Glue appeals to people who want to go completely serverless and are fine with staying within the AWS ecosystem using only AWS services. It appeals especially to the companies who do not want to spend money on infrastructure teams to closely monitor and manage their ETL system. The downside is that data completely resides in the cloud and may not be suitable for industries with high compliance requirements and hybrid cloud ambitions.

AWS Glue Pricing

AWS Glue has a pay-as-you-go pricing model. It charges an hourly rate, billed by the second. The pricing is in terms of data processing units which are charged at 0.44 per DPU hour. Read more about AWS Glue pricing here.

7. StreamSets

Key Features of StreamSets

  • StreamSets positions itself as a DataOps tool. It has data monitoring capabilities that stretch beyond the traditional ETL.
  • Cloud-optimized, real-time ETL tool.
  • Utilizes a spark-native execution engine to extract and transform data. Customers can build batch and real-time data pipelines with minimal coding.
  • Stream sets support a large number of origin and destination combinations. A list of all supported origin and destination can be found here.
  • Support for SAAS offerings is limited in the case of stream sets.
  • Stream sets come with a data protector offering that complies with major data security guidelines like HIPAA and GDPR.

SteamSets Use Case

StreamSets is a good option in case the use case is completely real time-oriented and the organization does not want to be locked into a particular cloud provider. It allows companies to use their own preferred on-premise or cloud provider and use StreamSets only for defining their real-time pipeline. If you are using a large number of SaaS offerings, StreamSets are not a preferred option since SaaS connector support is not comprehensive.

StreamSets Pricing

StreamSets pricing is not disclosed and is based on negotiated contracts.

8. Blendo

Key Features of Blendo

  • Real-time, cloud-native ETL tool.
  • Blendo focusses on extraction and syncing of data of ELT. It extracts raw data from sources and loads it into destinations without performing transformations.
  • Blendo has over 50 data sources, majorly focussing on SaaS platforms and databases.
  • Blendo does not focus much on the compliance part and does not make any claims about data security compliances.

Blendo Use case

Blendo is a good option in case the company wants an ETL tool for great support for SaaS offerings and does not have strict compliance requirements to maintain data on-premise.

Blendo Pricing

Blendo base package starts at 150$ per month. You can read more about Blendo pricing here.

9. Google Cloud Dataflow

Key Features of Google Cloud Dataflow

  • Google cloud dataflow is a fully managed ETL service provided by Google based on Apache Beam.
  • It is tailor-made for google cloud ecosystem sources and destinations.
  • It works well for batch as well as real-time use cases.
  • Using Dataflow, it is possible to run a completely serverless ETL pipeline based on google ecosystem components.
  • Google cloud platform complies with all data security guidelines like HIPAA and GDPR.
  • Since it is designed for the google cloud ecosystem, it does not fare well on the multi-cloud and hybrid cloud-based architectures.

Google Cloud Dataflow Use case

Google Cloud Dataflow is a good alternative if the company does not mind being locked down to the Google ecosystem and does not have strict compliance requirements with respect to on-premise data. Dataflow makes sense in scenarios where the customer is not interested in managing their own infrastructure and wants a serverless ETL model.

Google Cloud Dataflow Pricing

Google cloud dataflow is billed on a per hour basis for CPU, memory, storage, and data processing units. You can find more details of its pricing here.

10. Azure Data Factory

Key Features of Azure Data Factory

  • Azure data factory is the Microsoft counterpart for AWS Glue and Google Cloud Dataflow.
  • It is a fully managed service focusing more on Azure-based destinations.
  • It supports both real-time and batch-based ETL flows.
  • Data factory can run a completely serverless ETL pipeline using Azure components.
  • Like its AWS and Google cloud counterparts, it complies with almost all data security guidelines.
  • Azure data factory is not suited for multi-cloud or hybrid cloud-based architectures.

Azure Data Factory Use case

Data factory is a good alternative for people well invested in the Azure ecosystem and does not mind being locked to it. Customers who are comfortable with data being on Azure cloud and do not have multi-cloud or hybrid cloud requirements can prefer this.

Azure Data Factory Pricing

Azure data factory is priced based on the number of activity runs per month. You can find more details about the pricing here.

11. Apache Nifi

Key Features of Apache Nifi

  • Apache Nifi is an open-source data flow automation software that can be used to execute ETL flows between various sources and destinations.
  • It is more suited for real-time processing with rudimentary support for batch-based processing.
  • Support of integration to SAAS offerings is not present in Apache Nifi. Since it is open-source, developers can build them using custom implementations.
  • Apache Nifi is not locked to any cloud provider and can practically run on on-premise, or in any cloud provider. 
  • All compliance and data security become the responsibility of the infrastructure team when Nifi is deployed on-premise.

Apache Nifi Use case

Data factory is a good alternative for people well invested in the Azure ecosystem and does not mind being locked to it. Customers who are comfortable with data being on Azure cloud and do not have multi-cloud or hybrid cloud requirements can prefer this.

Apache Nifi Pricing

Azure data factory is priced based on the number of activity runs per month. You can find more details about the pricing here.

Before you dive into understanding what the top ETL solutions in the market today offer, it is important to briefly understand the ETL process itself. This will set you up better to appreciate the value provided by different ETL tools. 

What is ETL?

ETL simply stands for – Extract, Transform, and Load. It is the process of moving raw data from one or more sources into a destination data warehouse in a more useful form. This is an essential process in making the data analysis-ready in order to have a seamless business intelligence system in place.

Often, the process entails the following: Data is first extracted from the source and maintained in a staging area. While in the staging area, depending on the use case of your business, the data is transformed into a format that’s more useful for analysis and more appropriate for the destination warehouse schema. It is then loaded into the destination data warehouse. You can aslo read more about the ETL Testing.

What are ETL Tools?

What is ETL Tool ? ETL tools are applications/platforms that enable users to execute ETL processes.  In simple terms, these tools help businesses move data from one or many disparate data sources to a destination. These help in making the data both comprehensible and accessible (and in turn analysis-ready) in the desired location – often a data warehouse.

Selecting an ETL tool is a make or break decision for companies because if not done carefully,  this can become a cost that . Good ETL tools automate most of these workflows without needing human intervention at all and provide a highly available service.

Now that we know what an ETL tool is, let us look at the list of top ETL tools and go through a quick comparison of these.

If your organization is taking steps to migrate some or all of their OLTP and OLAP assets to more modern solutions and you are looking for a modern ETL solution with ability to integrate with a variety of sources, real-time data streaming, robust data transformations, zero data loss, easy etup and minimal supervision, then a hassle-free, modern data integration platform like Hevo might suit your needs. Hevo brings data from 100s of disparate data sources into your data warehouse in real-time without the need of writing a single line of code. 

What are your thoughts on the ETL tools shared in this blog? Which is the ETL tool of your choice? Let us know your thoughts in the comments.

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