Why Should You Use Data Extraction Tools?
What Does Data Extraction Software Do?
It is nearly impossible to purchase a tool that does only data extraction. The most basic of these tools also transforms the data and load it into another system. In the early days of data mining, many data extraction vendors marketed their products as ETL (short for extract, transform, load), or data migration tools. Over the years, most vendors have added more capabilities to their tools and now call them data integration and/or data pipeline tools, although the core capabilities remain the same.
It’s worth noting that many data fabric and data management platforms also incorporate data extraction and data integration features. However, some organizations find it useful to have separate data extraction software. These standalone tools sometimes offer better performance and can be more affordable if organizations don’t need the full capabilities of a more advanced data platform.
The list below focuses on tools whose primary purpose is data extraction, rather than more broad capabilities.
How to Select Data Extraction Tools
If you are in the market for data extraction software, keep these tips in mind:
- Determine your needs. Make sure you understand exactly why you are looking for data extraction software and what features you need it to have. Map out where it will fit in your big data and analytics workflows, so that you understand what other tools it needs to integrate with.
- Consider your staff’s level of expertise. Some data extraction tools are designed to be used by business analysts with no coding abilities, while others require more advanced knowledge. Make sure you get the right type of tool to suit your team’s abilities.
- Check the connections. When it comes to data extraction tools, nothing is more important than making sure it will connect to your data sources, as well as the software or cloud services you use for your data warehouse or data lake. Remember, the total number of connections isn’t as important as connecting to the actual applications and services that you use. And if a tool you are considering doesn’t connect to all your data sources, make sure you understand the difficulty involved in creating custom connections.
- Don’t confuse ELT and ETL. Some data extraction tools can do both ELT (the loading happens before data transformation) and ETL (the transformation happens before the loading), but some can do only one or the other. Make sure you are getting the right type of product for your needs.
With those tips in mind, here are ten data extraction software applications you might want to consider:
- Altair Monarch
- Domo Data Integration
Best Data Extraction Tools
Founded in 1985, Altair sells a variety of software, hardware and services, primarily related to data analytics, product design, high-performance computing and the Internet of Things. Its customers include NASA, RUAG Space, PING Golf, Specialized, Ford, Stanley Black & Decker, Kyoto University and others. Over the years, Altair has acquired a number of other technology companies, including Datawatch, the previous vendor of the Monarch software.
Part of the company’s data analytics lineup, Monarch is Altair’s “market-leading self-service data preparation solution.” It incorporates both data extraction, data cleansing, and transformation capabilities, and it offers more than 80 pre-built data preparation functions. It can extract data from PDFs and text files, as well as structured sources, and it requires no coding abilities. It is available in a variety of different versions and can be deployed in the cloud as software as a service or on premises.
An annual subscription to the Monarch Complete cloud service starts at $1,995. A free trial and demos are available. Prices for the server version are available on request.
- With its 30-year history, Monarch is one of the most mature data extraction tools available.
- The tool is easy to use.
- Monarch integrates with Altair’s other data analytics tools.
- Some customers complain that the cost is too high or wish that a “lite” version with fewer features were available at a lower price.
- Sometimes the tool experiences performance issues with very large datasets.
- Some customers say that they were not able to get the full benefit from the software until they also purchased training.
Domo is a business intelligence startup founded in 2010. It claims more than 1,800 customers, including DHL, ESPN, L’Oreal, Traeger, Zillow, Ebay, Comcast, Autodesk and others. It has won several awards, including Ventana Research Digital Leadership Award – Analytics and Best Business Intelligence Software Company from Digital.com.
Data extraction capabilities are included in Domo’s Data Integration product. Its key features include more than 1,000 pre-built connectors for cloud systems, fast query response times, automated data pipeline workflows, data federation and massively parallel processing. It also includes some data governance capabilities and offers strong security.
Pricing and a free trial are available on request. Prices depend on which Domo platform features you use, data volume, storage needs, refresh rates, query volumes and the number of users.
- The data extraction capabilities are part of a comprehensive data platform that integrates with Domo’s BI tools.
- Domo has built-in connectors for a lot of cloud and on-premise enterprise applications.
- The tool gets high marks from customers for its flexibility.
- The full Domo platform might be more than some organizations need, if they are just looking for ETL.
- The price can be high.
- Some customers say that new releases tend to be buggy.
Founded in 2013, Etleap is one of the few vendors on this list that still describes itself as an ETL vendor, although it also sometimes describes its product as data pipeline software. Its customers include Mode, Blink Health, LendingHome, Airtable, Pagerduty and others.
Domo makes it easy to create an ETL pipeline to build a cloud data warehouse on AWS Redshift or Snowflake. Key features include flexibility, scalability, coded or code-less transformation creation options, compliance, SSO integration and more. It integrates with more than 50 data sources, including MySQL, AWS, PostgreSQL, Oracle, Salesforce, Marketo, Jira, Hubspot and Hadoop.
Pricing and a free demo are available on request.
- Etleap’s tight integration with AWS makes it a good option for organizations with a data warehouse built in Redshift or Snowflake.
- It doesn’t have a lot of extraneous features, so it’s a good option if you really only want ETL.
- Training and support are available.
- The tool doesn’t have as many features as some of the other options on this list.
- Etleap doesn’t have a large customer basis, and few reviews are available online.
- It requires some advanced knowledge, so it’s not a good option for organizations that don’t have experienced engineers and architects setting up the data pipelines and data warehouse.
Founded in 2013, Fivetran is a pure-play startup that focuses on “simple, reliable data integration for analytics teams.” It has more than 1,000 customers, including Square, DocuSign, Lime, Spanx, Udacity and others.
The Fivetran platform offers fully managed ELT pipelines. Key extraction features include normalized schemas, incremental batch updates, 24-hour tech support, real-time monitoring, granular system logs, and a 99.9% uptime guarantee. It has more than 150 built-in connectors, including MySQL, Oracle, Amazon S3, Microsoft Dynamics, and many others, and it can pull data directly from more than 5,000 different cloud-based applications.
Fivetran lists pricing on its website, but the pricing method is complicated. The service costs $1/credit for the Starter version, $1.50/credit for Standard, and $2/credit for Enterprise. Credits are determined based on the monthly active rows, but as your volume increase, each credit covers more active rows. Free trials are available.
- Fivetran claims that most users can set up the service in just five minutes.
- The pay-as-you-go pricing makes it easy to scale.
- The 99.9% uptime SLA provides confidence that data will always be available for analysts.
- Customers say that Fivetran’s transformation capabilities are not as advanced as its extract and load capabilities.
- The company provides upfront pricing by keeping track of your actual usage can be difficult.
- Sometimes syncing takes longer than expected.
Based in the Czech Republic, Keboola offers a data operations platform that includes storage, sharing, transformations and data science capabilities. Its customers include Mall Group, Kiwi.com, Platterz, Heureka, Firehouse Subs, Hello Bank! and others.
Keboola can perform ETL or ELT jobs. It promises fast deployment, enterprise-grade security, automation, an open platform, “scaffolds” for connecting to common data sources, data catalog capabilities, a developer portal and more.
Keboola offers a free plan with 300 free minutes each month, with paid overages after that. The subscription plan adds more features and starts at $2500 per month.
- Keboola offers more breadth of capabilities than some of the ETL-only tools.
- Customers applaud Keboola’s excellent service.
- The free tier is a big plus for organizations that are just getting started with data pipelines.
- Keboola’s interface isn’t as easy to use as some other options.
- Some customers complain that it isn’t as easy to integrate into their continuous integration workflows as they would like.
- Keboola promises fast setup, but onboarding isn’t as fast or easy as with some competing services.
Matillion describes itself as a cloud-based ETL software provider. Founded in 2010, it has amassed an impressive customer list that includes The Home Depot, Travis Perkins, GE, Siemens, Western Union, Splunk, Ikea, Cisco, Amazon, Merck, Accenture and others. Gartner named it a Niche Player in its Magic Quadrant for Data Integration tools.
Matillion natively integrates with AWS Snowflake and Redshift, Google BigQuaery, Microsoft Azure Synapse and other cloud services, making it easy to feed data into a data warehouse. It supports advanced transformations and has a long list of pre-built connectors for data sources.
The software is available in two different versions: Data Loader is a free version with basic capabilities, and ETL is the paid version. The ETL version has four different pricing tiers: Medium ($1.79 per hour), Large ($3.49 per hour), XLarge ($6.49 per hour) and Enterprise (pricing on request). A demo is available.
- Matillion is very easy to use.
- Performance is very fast, often faster than multi-function tools that do more than ETL.
- The upfront pricing makes it easy to estimate costs.
- Customers complain about slow and/or poor customer support.
- Error messages are difficult to understand.
- Documentation is inadequate to customer needs.
Founded in 2015, Panoply offers a cloud data platform that allows small to medium-sized businesses to create data warehouses. Its customers include Kaplan, Spanx, Shinesty and others. It has won several awards, including being named a Gartner Cool Vendor in 2019.
This platform combines data extraction and integration with full data warehouse capabilities, and some versions also include data governance features. It offers connectors for more than 60 data sources, and it promises world-class security and 99.99% uptime. Other features include fully managed syncing and storage, automatic data type detection, built-in performance monitoring, high scalability and pre-built SQL queries.
Panoply comes in Lite ($200 per month), Starter ($325 per month), Pro ($665 per month), Business ($995 per month) and Enterprise (pricing on request) versions. All offer a free 14-day trial.
- Panoply is one of the highest-rated data extraction tools on the market.
- Its customer service team gets high marks from customers.
- The tool makes connecting data sources very easy.
- While it is well-suited for most SMB needs, it doesn’t have the more advanced features that large enterprises might need.
- It doesn’t have as many built-in connectors as some of the other options available.
- Some customers say they wish it had data visualization capabilities.
Rivery describes its platform as a “real-time data pipeline,” and it offers cloud-based ETL, data migration and data orchestration capabilities. Its customers include Bayer, the American Cancer Society, Minute Media, WalkMe and others.
On its list of benefits, Rivery touts its ability to ingest data from any source, scalability, speed, low cost and simplicity. It designed its ETL tool to be used by business users without assistance form DevOps teams, and it is compatible with AWS Snowflake and Redshift, Google BigQuery and Microsoft Azure.
Rivery offers some pricing details on its website, but the information is not very specific. It says its Base package costs between $10 and $50,000 per year with a free trial available, and pricing for the Enterprise package is available on request.
- Rivery gets very high reviews from customers.
- Its customer support is top notch.
- The interface is user-friendly.
- Setting up a new data source can be time-consuming.
- Rivery’s documentation is not very clear.
- The pricing on its website is vague and not very transparent.
Now owned by unified data fabric vendor Talend, Stitch offers “simple, extensible ETL.” While Talend and Stitch products integrate well together, Stitch still operates as an independent business unit. Its customers include Peloton, Envoy, Invision, Indiegogo, Instapage and Postman.
This fully managed data pipeline integrates with more than 130 data sources, and the company sponsors the Singer open source framework, which makes it easy to build integrations with other applications. Stitch doesn’t require any coding, and you can set it up in minutes. It offers orchestration, security, compliance, and data quality features.
Stitch Standard starts at $100 per month for 5 million rows of data, climbing up to $1,250 per month for 300 million rows. Discounts are available for an annual purchase, and the company offers a free 14-day trial. Prices for Stitch Enterprise are available on request.
- Stitch has a long list of integrations and makes it easy to integrate with other data sources that don’t have built-in support.
- Its customer service gets very good reviews.
- Stitch’s pricing is very affordable.
- Customers say they would appreciate better data filtering capabilities.
- It has limited data transformation capabilities.
- Some customers also would like to see better logging and error handling.
Calling itself the “most advanced data pipeline,” Xplenty offers both ELT and ETL capabilities. It is a pure-play startup founded in Isreal in 2012. Its customers include Gap, Samsung, Philip Morris International, PWC, Masterclass, Deloitte, Accenture, Ikea and others.
Xplenty offers a complete data pipeline toolkit that includes orchestration and monitoring capabilities. It integrates with more than 140 data sources and is particularly well-suited to organizations that use Salesforce. It is highly scalable has advanced customization capabilities.
A demo is available and pricing are available on request.
- Xplenty’s close Salesforce integration make it a good option for organizations that use a lot of Salesforce services.
- The tool gets kudos from customers for being easy to use.
- The customer support is very good.
- Customers with very large datasets can encounter scalability problems.
- Logging and error reporting aren’t as robust as they could be.
- Documentation is lacking.
Data Extraction Software Comparison Table
Data Extraction Software
· Mature product
· Easy to use
· Integrates with other Altair tools
· High price
· Poor scalability
· Requires training
· Comprehensive features
· Lots of connectors
· Too many features for some
· High price
· Buggy releases
· AWS integration
· ETL only
· Training and support
· Limited features
· Few customer reviews
· Requires technical knowledge
· Fast setup
· Pay-as-you-go pricing
· 99.9% uptime SLA
· Limited transformation capabilities
· Estimating pricing can be
· Slow syncing
· Broad capabilities
· Good customer service
· Free tier
· Not easy to use
· No CI support
· Slow onboarding
· Easy to use
· Fast performance
· Upfront pricing
· Slow customer support
· Poor error handling
· Inadequate documentation
· Highly rated
· Good customer support
· Easily connects to data sources
· Not great for enterprises
· Limited connectors
· No data visualization
· Good reviews
· Good customer support
· Easy to use
· Time-consuming setup
· Poor documentation
· Vague pricing
· Highly extensible
· Good customer support
· Limited filtering
· Limited data transformation
· Poor logging and error reporting
· Salesforce integration
· Easy to use
· Good customer support
· Scalability problems
· Poor logging and error
· Inadequate documentation