

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
The incidents have disappeared completely since I have been using Striim.
Striim's continuous pipeline safely processes millions of daily transactions without data loss; my organization had millions of transactions every day and even in real-time, so it was quite good.
Since it is now one to two hours, I would say it has saved employee hours and time.
There is a clear return on investment because there is a significant amount of time saved and productivity gained, with roughly 30% to 50% of the time being reduced in solving production tickets heavily dependent on ad-hoc queries and accessing data from multiple sources.
If they contain duplicate counts or null records or improper data, those records would not be reliable.
Tasks such as querying data, validating results, and troubleshooting database issues became more efficient, which helped save time during development and testing.
They are all knowledgeable about what they do.
When you contact them, they give you a response straight away and help you identify the issue and fix it.
The customer support has been excellent, and their engineers actually understand z/OS architecture and DB2 logs.
The quality of their support is excellent, and the speed is very good, too.
They resolved my issue within a day which was specifically around licensing.
Overall, the service is excellent.
Our licensing was based on the number of cores, so even if we have a high number of events on any given day, our license cost would not go high.
I would describe the scalability of Striim as very good, as it adapts well.
Striim can handle the data volumes effectively, but it can struggle a little bit if the data volume is too high.
It does not scale well when considering the high cost of the Mac license.
Some aspects, like scalability, could be improved to avoid writing different codes for each database.
Scalability has not been an issue because so far we have dumped about a billion records per year, and I do not see any issues as such.
That problem has been completely resolved with Striim.
Striim was very stable.
In my experience, Striim is mostly stable.
Toad Data Point has been stable overall in my experience, especially for regular database querying and daily development tasks.
Most of the time, it performed consistently when running queries, connecting to data sources, and analyzing data.
I often feel instability locally because it is a heavy application, and I feel some slowness in the response of the user interface.
I believe if Striim could use some part of AWS secrets or its own secret mechanism to store the password, that would really save a lot of time so that I don't have to keep updating the password whenever there is any change.
They could improve the documentation by showing how to configure with different platforms.
I think Striim could be improved with better pricing and enhanced documentation.
Better data visualization tools, improved integrations with modern tools, and enhanced collaboration features such as shared query libraries and real-time collaborations would be beneficial.
Toad Data Point should include more features for utilizing AI, which can automatically perform many tasks.
The application is heavy on my local PC; however, if I connect to a remote server, I think it works better.
Licensing was a bit more expensive because Striim has to read from Oracle GoldenGate trail files and also integrate them.
My experience with the pricing, implementation cost, and licensing of Striim is that it is somewhat expensive.
It's very fair.
The Mac licenses are expensive, costing 1,600 dollars each.
The pricing for Toad Data Point is where it gets into trouble.
The pricing is cost-effective; it is neither too cheap nor too expensive, it's a good value.
Striim is capable of absorbing a large number of transactions, and the difference between the two databases is always less than a second, which demonstrates efficiency.
There were significant improvements because once we enabled change data capture, the database was not going down at all.
It reduces manual intervention because it automatically syncs the data from the warehouse.
I am able to have cross-connection queries, blend and join data from multiple different databases in a single query, with data profiling, automation and scheduling, and export and reporting tools.
I utilize automations in my database with Ansible automations, performing automation data processing units and deployment, which has a positive impact, increasing efficiency and reducing human error, as well as saving time, thus improving productivity and scalability compared to human errors.
Broad connectivity with the visual query builder because it is the most valuable for me as I can connect to different data sources, build queries quickly with drag-and-drop, and validate the results without writing everything manually from scratch.
| Product | Mindshare (%) |
|---|---|
| Toad Data Point | 0.8% |
| Striim | 0.6% |
| Other | 98.6% |

| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 1 |
| Large Enterprise | 11 |
Striim offers a comprehensive platform for real-time data integration and streaming analytics, designed to streamline data processes for enterprise-level solutions.
Striim enables seamless migration and integration of data across cloud and on-premises environments, making it ideal for businesses looking to leverage real-time analytics. Its capabilities support continuous data flow, reducing latency and enhancing decision-making. Designed for scalable and secure data management, Striim facilitates effective data-driven strategies.
What are some key features of Striim?In industries like finance, Striim supports real-time fraud detection by providing uninterrupted data streaming between transaction systems. In healthcare, it enables rapid data processing for patient monitoring, improving service delivery. Manufacturing uses Striim to enhance supply chain visibility through real-time data analytics.
Toad Data Point offers a user-friendly platform for streamlined database management, providing effective tools for data integration and analysis across multiple databases.
With a focus on enhancing database management efficiency, Toad Data Point facilitates smooth SQL querying and data preparation for organizations. Its seamless integration with different databases like Oracle, DB2, and MySQL allows for effective data analysis and workflow automation. Users benefit from drag-and-drop query building and AI-assisted analysis, enhancing productivity while enabling data-driven decision-making.
What are the key features of Toad Data Point?In industries requiring extensive data analysis and reporting, Toad Data Point is deployed to streamline operations. Businesses engage it for SQL queries, data preparation, and cross-database analysis, which are critical for sectors reliant on accurate data and timely insights.
We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.