What are our data sources?
We use the data sources on the side for ranking solutions and awarding badges in data observability tools category. Our data sources in data observability tools category include;
Data observability software or tool allow companies to manage, track and understand their data within a system. Data observability tools play an important role within DataOps to improve the quality of data-flow. They help companies:
To be categorized as data observability software, a product must:
AIMultiple is data driven. Evaluate 16 services based on
comprehensive, transparent and objective AIMultiple scores.
For any of our scores, click the information icon to learn how it is
calculated based on objective data.
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We use the data sources on the side for ranking solutions and awarding badges in data observability tools category. Our data sources in data observability tools category include;
review websites
social media websites
search engine data for branded queries
According to the weighted combination of 7 data sources
Integrate.io
Monte Carlo
DQLabs Data Quality
Bigeye
Taking into account the latest metrics outlined below, these are the current data observability tools market leaders. Market leaders are not the overall leaders since market leadership doesn’t take into account growth rate.
Integrate.io
Monte Carlo
DQLabs Data Quality
Bigeye
These are the number of queries on search engines which include the brand name of the solution. Compared to other Data categories, Data Observability Tools is more concentrated in terms of top 3 companies’ share of search queries. Top 3 companies receive 100%, 27% more than the average of search queries in this area.
25 employees work for a typical company in this solution category which is 4 more than the number of employees for a typical company in the average solution category.
In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 1 companies with >10 employees are offering data observability tools. Top 3 products are developed by companies with a total of 35 employees. The largest company building data observability tools is Xplenty with more than 20 employees.
Taking into account the latest metrics outlined below, these are the fastest growing solutions:
Monte Carlo
Integrate.io
DQLabs Data Quality
Bigeye
We have analyzed reviews published in the last months. These were published in 4 review platforms as well as vendor websites where the vendor had provided a testimonial from a client whom we could connect to a real person.
These solutions have the best combination of high ratings from reviews and number of reviews when we take into account all their recent reviews.
This data is collected from customer reviews for all Data Observability Tools companies. The most positive word describing Data Observability Tools is “Easy to use” that is used in 2% of the reviews. The most negative one is “Difficult” with which is used in 1.00% of all the Data Observability Tools reviews.
According to customer reviews, most common company size for data observability tools customers is 51-1,000 employees. Customers with 51-1,000 employees make up 55% of data observability tools customers. For an average Data solution, customers with 51-1,000 employees make up 50% of total customers.
These scores are the average scores collected from customer reviews for all Data Observability Tools. Data Observability Tools is most positively evaluated in terms of "Customer Service" but falls behind in "Ease of Use".
This category was searched on average for 575 times per month on search engines in 2022. This number has increased to 734 in 2023. If we compare with other data solutions, a typical solution was searched 1k times in 2022 and this increased to 1.2k in 2023.