Overwhelmed while choosing the right data transformation tool for your business? Don’t worry, I’ve got you covered.
Data transformation is one of the most crucial steps in data integration, and data transformation tools play an important role.
Choosing the right data transformation tools is a game-changer, and getting it wrong can have serious consequences. We all know that data is the lifeblood of any business. The real trick is getting that data to your people with the right tools in a form they can directly use.
In this article, I’ll share my top picks for data transformation software available in the market.
Let’s get started!
What are Data Transformation Tools?
- Data transformation tools are software applications that alter or update your data from one state to another to fit your specific needs.
- For example, in the image given, you can change the data type of the third column using a transformation tool, either through automation or custom scripting.
What is the need for Data Transformation Tools?
- The core challenge? You juggle between diverse data sources, tackling data quality issues, managing massive volumes of data, and dealing with different data formats and structures—all while staying efficient. It’s a puzzle that needs solving!
- Therefore, you need these transformation tools to cleanse, modify, and enrich data without causing data loss.
- For example, if you need to conduct a thorough financial analysis, consolidating data from accounting software, billing systems, payroll records, and financial market data is necessary.
Given the example, next, I have mentioned the benefits of using data transformation tools.
Benefits of Data Transformation Tools
- Improved Data Quality: Data transformation tools can validate, cleanse, and reformat your data to prevent errors like old data, null values, erroneous indexing, duplication, and corruption, effectively maintaining data integrity.
- Enhanced Data Integration: You can easily combine data from various sources into a unified view, allowing various platforms, applications, and processes to use it.
- Scalability: These transformation tools let you scale large volumes of data efficiently as your business grows by removing bottlenecks in the data flow.
- Better Organization: You can easily manipulate and analyze data in different formats, making it understandable for both humans and computational tools.
- Increased performance: Data transformation tools can help you declutter datasets and remove unnecessary elements, hence improving technical performance for faster processing and gaining valuable insights.
These benefits clearly showcase how data transformation software empowers your business to unlock its data’s full potential. It converts raw data into actionable insights, making it easier for you to make informed decisions that drive business success.
(EdQ)
What are the categories of Data Transformation Tools?
Before I discuss my top picks, it’s essential to consider the different use cases and market segments for these transformation tools. Finding the right tool for you depends on factors like budget, organization size, project scope, and technical expertise available.
Data Transformation Tool is a broad category which is further sub-divided into 4 sections, namely:
Automated Transformation Tools
- Hevo Data and Matillion are the best tools for automated transformation.
- Automated tools help you convert and clean data automatically.
- Handling repetitive tasks without manual effort saves you time.
- These tools ensure your data is accurate and ready for analysis.
- They also allow you to focus on more important tasks while they manage the data transformation.
Enterprise Transformation Tools (COTS)
- Snowflake, AWS Glue, and Talend are the leading enterprise transformation tools.
- These tools are powerful software designed for big businesses.
- They must perform extensive data transformations, usually to centralize and store data in a data warehouse.
- These tools require minimal setup and configuration, and they help you to quickly turn raw data into valuable insights without a lot of extra work.
Open Source Transformation Tools
- dbt, Airbyte, and Apache Kafka are popular open-source transformation options.
- Free and customizable software that you use to transform data.
- They let you modify and improve the tool’s underlying source code to fit your needs.
- With community support, you can find solutions and add new features.
- These tools help you manage data without the cost of commercial software.
Custom Transformation Solutions
- Python and PostgreSQL are the hard-code options that can be used to build custom transformation solutions.
- You built these solutions from scratch for your business’s specific use cases.
- You work with developers to create tools that perfectly fit your data processes.
- These solutions offer flexibility and precise functionality, effectively helping you handle unique data challenges.
Top 10 Data Transformation Tools
1. Hevo Data
G2 Rating: 4.3/5.0
Hevo Data is a cloud-based tool for ETL and ELT data pipelines. Its easy-to-use, no-code interface is cost-effective and lets you replicate data from over 150 sources almost in real-time. Hevo offers two methods for data transformation before it is loaded to the destination: Python code-based transformations and drag-and-drop transformations.
Key Features
- Near Real-Time Replication: On all plans, you get near real-time replication. For database sources, it’s near real-time through pipeline prioritization. For SaaS sources, near real-time replication depends on API call limits.
- In-built Transformations: With Hevo, you can format your data quickly using the drag-and-drop interface or the easy Python interface. You can also create analysis-ready data in your warehouse with Hevo’s Postload Transformation.
- Monitoring and Observability: You monitor pipeline health with intuitive dashboards showing every pipeline stat and data flow. You also get real-time visibility into Your ETL with alerts and activity logs.
Pricing
- Hevo Data charges you for every event inserted or updated in the warehouse. It lets you stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow.
- Hevo’s pricing plan starts at $0/month for up to 1M events/month.
Discover clear, upfront pricing with no surprises, no matter how much you grow. Enjoy a 14-day free trial and round-the-clock support with Hevo today!
2. Matillion
G2 Rating: 4.4/5.0
Matillion is an ETL tool that simplifies data processing for Amazon Redshift, Azure Synapse, Snowflake, and Google BigQuery. It helps you transform raw data into valuable insights, bridging the gap between your data sources and your BI tools.
Key Features
- Multi-language coding IDE: You can easily create custom transformations without errors. Our high-code SQL IDE automatically checks all SQL statements for you, ensuring accuracy and speed.
- GitHub Integration: Improved collaboration with GitHub lets you easily push transformations across your data projects and manage version control directly within the platform.
- Scheduling: You can automate and schedule data pipelines based on custom parameters. These allow you to run pipelines at fixed times periodically.
Pricing
With Matillion, you can have unlimited users, environments, and scalability, paying only for what you use. Whether it’s for a specific project or your entire data team, Matillion adjusts to your needs. Its basic plan starts at $2.00/month for 500 credits.
3. Snowflake
G2 Rating: 4.5/5.0
Snowflake is a cloud platform for centralizing, storing, and transforming all types of data. It offers an efficient and secure processing engine and supports various query languages, such as SQL, for you to manage large and diverse datasets.
Key Features
- Time Travel: This feature allows you to access historical data, view it, and query it as it existed before alteration or deletion in a certain time period. This ensures data integrity and reduces errors.
- SQL Support: Snowflake supports many SQL features such as data manipulation, query optimization, etc., which ensures you can effectively manage, transform, and analyze your data.
- Scalability: With Snowflake’s auto-scaling feature, you can seamlessly process large datasets and accommodate high concurrency without performance degradation, ensuring your transformation processes remain fast and reliable regardless of data volume.
Pricing
At Snowflake, you get a consumption-based pricing model, so you only pay for what you use. This gives you the flexibility to scale up or down as needed and see exactly how much you’re using and spending. Their Enterprise Plan starts at $3.00/ per credit.
4. AWS Glue
G2 Rating: 4.2/5.0
Glue is a serverless ETL tool in Amazon Web Services (AWS). It works well with S3 and Athena to analyze and categorize data. AWS Glue is a stable and reliable data transformation tool that helps developers like you build data catalogs.
Key Features
- Visually transform data: Define your ETL process on a job canvas and generate code automatically to extract, transform, and load your data.
- Simple Job Scheduling: You can build complex ETL pipelines after invoking AWS Glue jobs on a schedule, either on-demand or per-event basis.
- Built-in Job Notebooks: AWS Glue job notebooks give you serverless notebooks with easy setup, so you can start quickly.
Pricing
With AWS Glue, you pay by the second at an hourly rate for using crawlers to discover data and for ETL jobs to process and load data. For the AWS Glue Data Catalog, you pay per month to store and access your metadata. The first million objects and the first million accesses are free.
5. Talend
G2 Rating: 4.3/5.0
Talend is a big data and cloud data integration tool that offers data extraction, transformation, and loading within a unified platform. It can enhance your workflow by incorporating real-time data transformation and works with top cloud services like Google Cloud, AWS, and Snowflake.
Key Features
- Drag-and-Drop Interface: This feature allows you to visually map out data transformations using its pre-built connectors. It enables you to easily connect data sources, apply transformation logic, and define data destinations without the need for extensive coding.
- Data Quality Tools: The comprehensive set of tools in Talend ensures that your data is accurate, consistent and reliable by helping in profiling, cleansing, and enrichment of data.
- Flexibility: It works with different setups, such as on-premises, cloud, multi-cloud, and hybrid, so you can use it to transform data anywhere regardless of your organization’s infrastructure.
Pricing
To perform real-time data capture, movement, transformation and unification, you’ll need to contact them to build a custom pricing. While the no-code data ingestion plan starts at $100/month.
6. dbt
G2 Rating: 4.8/5.0
dbt, the Data Build Tool, is a command-line tool made for SQL and Python experts. Its sole purpose is to make your data transformation task simple and fast. It follows software best practices, like adding new features and automating processes like Continuous Integration and Continuous Delivery (CICD).
Key Features
- dbt Cloud IDE: The dbt IDE combines creating, testing, running, and tracking dbt projects in one online interface, making it easier for both new and experienced developers like you.
- Models: If you know how to write SQL SELECT statements, you can build a model. Models are instructions written in SQL that help you create complex data pipelines. You can use them to group, select, combine, and change data.
- Code Reuse: With dbt, you can use macros, which are like ready-made pieces of SQL logic that you can use over and over again. Macros help you bundle up common changes or calculations so you can use them in different parts of your work.
Pricing
dbt pricing starts at $100/month/seat for a team of up to 8 developers seats and 15,000 successful models built per month.
7. Airbyte
G2 Rating: 4.5/5.0
Airbyte offers both a cloud-based platform and a self-hosting option. While Airbyte doesn’t include built-in data transformation features, you can integrate it with dbt to perform advanced data transformations independently.
Key Features
- Built Custom Connectors: Airbyte provides the option of creating a custom connector if your preferred connector is not in the pre-built list. Options like CDK, language-specific CDK, and a no-code connector builder allow for quick development of tailored connectors.
- Debugging Autonomy: You can modify and debug pipelines whenever you want, without waiting.
- Extensible: With open-source, you can edit existing connectors and create new ones. You won’t need separate systems anymore, Airbyte handles everything, including databases.
Pricing
With Airbyte Cloud, you pay based on what you sync. This covers any data that you create, update, or delete. As your usage increases, the price scales accordingly. For $2.50 per credit, you can synchronize data equivalent to 1/6 million rows for APIs or 250MB for databases and files.
8. Apache Kafka
G2 Rating: 4.5/5.0
Apache Kafka is a strong, free platform for event-driven data pipelines and transformation flows, along with its component, Kafka Connect. It uses five core APIs for common real-time data transfer and analysis functions. It’s a great choice if you have real-time applications and other important uses.
Key Features
- Scalability: Kafka is horizontally scalable which allows you to add hundreds of new servers for handling large data sets. This helps in the parallel processing of different transformations.
- Connector Transformations: You can configure connectors with transformations to make quick, single-message modifications. This is useful for adjusting data and routing events. You can also specify a sequence of transformations directly in the connector configuration.
- Real-Time Transformations: You can perform real-time data transformations on streaming data, ensuring that data is processed and transformed immediately as it flows through the system. This is achieved due to Kafka’s low latency and high throughput.
Pricing
Apache Kafka is an open-source software licensed under the Apache License 2.0. It is free for you to use, but you might need to pay for hosting and managing the infrastructure it needs.
9. Python
G2 Rating: 4.8/5.0
Python is a popular programming language among data professionals like you because it’s easy to work with indexed data structures and dictionaries, which are important for building ETL processes.
Key Features
- High-Level Language: When you write programs in Python, you don’t have to worry about the system architecture or manage the memory.
- Standard Library: Python offers various modules and libraries like Matlab, NumPy, Pandas, Tensorflow, etc., so you don’t have to re-write codes from scratch.
- Interpreted Language: You can easily debug the code without compilation as the source code is executed line by line and converted into byte code.
Pricing
Python is made available under an open-source license approved by the Open Source Initiative (OSI). This means you can use and distribute Python freely, even for commercial purposes.
10. PostgreSQL
G2 Rating: 4.4/5.0
Postgres is a powerful, open-source database management system that supports SQL and JSON-based querying. It’s widely used in big data, analytics, web, mobile, and other applications, making it great for storing your information in custom data transformation projects.
Key Features
- Wide Range of Data Types and Flexibility: PostgreSQL provides many built-in data types and allows you to define your own custom types.
- Reliable Transaction Support: PostgreSQL follows the ACID principles and offers features like layered transactions, savepoints, and different isolation levels, giving you control over how your transactions are managed.
- Fault-Tolerance and High Availability: It offers different ways to copy your data, like streaming it to another location. This ensures that even if one copy fails, you still have access to your information.
Pricing
PostgreSQL is licensed under the OSI-approved PostgreSQL License. You can use it for free, even in commercial software products.
How do you choose the right Data Transformation Tool?
- Step 1: Ensure the tool supports your business’s data formats and sources.
- Step 2: Pick a tool that can handle your increasing data volumes.
- Step 3: The tool should have a user-friendly interface and intuitive workflow to simplify your data transformation tasks.
- Step 4: Next, check the tool’s processing speed and efficiency to see whether it meets your data transformation needs on time.
- Step 5: Ensure the tool’s compatibility with your existing systems and tools.
- Step 6: Opt for tools that provide data validation, cleansing, and enrichment to ensure your data remains accurate and reliable.
- Step 7: Select tools that can be customized and adjusted to fit your business processes and needs.
- Step 8: Consider all expenses, including licensing fees, setup costs, and ongoing maintenance.
You can choose the right transformation tool according to your needs by considering these factors.
Additional Resources on Data Transformation Tools
Conclusion
As we wrap up this blog, I’ve shared my top picks for data transformation tools, each categorized for your convenience. Plus, I’ve included a handy checklist to help you choose the perfect tool for your needs.
You can SIGN UP FOR A 14-DAY FREE TRIAL with Hevo to experience how you can transform your data without the need to code.
FAQs
Q1. Which tool is used to transform data?
Tools like—Hevo Data, Matillion, Snowflake, AWS Glue, Talend, dbt, Airbyte, Apache Kafka, Python and PostgreSQL are used to transform data.
Q2. Is Python an ETL Tool?
Python offers various modules and libraries like Matlab, NumPy, Pandas, Tensorflow, etc., which contain tools that streamline the ETL process.
Q3. What is an ETL Tool?
ETL refers to the process of extracting, transforming and loading data. The tool used to perform these processes is called an ETL Tool.
With over a decade of experience, Sarad has been instrumental in designing and developing Hevo's fundamental components. His expertise lies in building lean solutions for various software challenges. Sarad is passionate about mentoring fellow engineers and continually exploring new technologies to stay at the forefront of the industry. His dedication and innovative approach have made significant contributions to Hevo's success.