Amplitude Analytics is an analytics platform for mobile and web. It is designed to help organizations segment users and analyze funnels, retention and revenue. Amplitude Analytics helps product marketers to achieve actionable insights from customer digital journeys and uses behavioral graphs to build customer-focused products. Amplitude also optimizes digital products for increased quality engagements, increased conversion rates, and long-term customer loyalty.
$61
per month
Google BigQuery
Score 8.7 out of 10
N/A
Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Pricing
Amplitude Analytics
Google BigQuery
Editions & Modules
Plus
$49
per month (paid annually)
Growth
Contact Sales
Enterprise
Contact Sales
Starter
Free
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
Offerings
Pricing Offerings
Amplitude Analytics
Google BigQuery
Free Trial
No
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Amplitude Analytics
Google BigQuery
Features
Amplitude Analytics
Google BigQuery
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Amplitude Analytics is an excellent solution for anyone with a mobile app and you want to track what users are doing, are they completing conversion steps, and are they coming back more often. This all helps you visual your customer bases engagement and help project future engagement and create goals. This also helps with prioritizing products to address drop-off points in the product to increase conversions.
Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).
GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
Seamless integration with other GCP products.
A simple pipeline might look like this:-
GForms -> GSheets -> BigQuery -> Looker
It all links up really well and with ease.
One instance holds many projects.
Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.
Some offerings seem duplicative, like dashboards and notebooks, which only seem to differ in that one can subscribe to dashboards
The messaging on valid vs invalid property types could be better explained to clarify which types (string, Boolean, integer, etc) are expected in particular scenarios. Though the type is usually set during event creation, we've often seen examples where the data received in production is different, leading to 'invalid type' errors
Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.
Great product Good value for the cost/initiate Support docs and FAQs are great - they limit the necessity of reaching out to in-person support. So when you do call them ... it is for a legit question/issue, no just a "where is it" or a "how to I do xyz123?"
We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
It's a fairly straightforward platform that's beginner friendly. The biggest usability hurdle is most often created by your own team, as it's imperative to know what event sources are being sent to Amplitude and what those event names are. Within being properly onboarded by a team member it can be hard to get started using Amplitude. It takes time to understand what data your company may be sending to the product, the naming conventions of events (especially if there are old or deprecated events names
I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.
Alway up and running, or if there is a problem we can get back in the game right away. The reliability was a big selling point for me, and it was true when this company got it. Rollouts can be tough, but this was pretty seamless. Good support throughout the process, good documentation to handle questions/tips
I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.
No issues, problems, or negative remarks from us!! We had a plan, vendor support was rock solid, our data folks have experience, OCM supported as needed, and we got the rollout done on time, on budget, and with only minor hiccups. SInce the rollout, most of us have already forgotten the hiccups and generally speak highly of the product
I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.
I haven't used the Amplitude support other than their training docs so I can't speak too much to the in-person support but the docs are serviceable. Nothing too crazy but between the user tips, email notifications, and the decent number of docs I was able to get the support I needed to ramp up on the tool.
BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
Virtual Not bad considering the timeframe and turnaround. The biggest benefit was for my end-users to hear a voice (other than mine/ours! LOL) telling them about the new features and capabilities. The in-person training was really good for having an expert that knows the answers and could refer to past experiences, problems, solutions. THey were a great resource to ease the transition ... basically a "you are gonna be okay with this change ... you got this etc.!" kinda vibe
Good enough to get strong baseline. I always make sure our our users go to and/or focus on the vebndor-provided support docs rather than any formal training. Our instructors come and go, but written policy and how-to docs live much longer in a corporate setting. That said, the online training is sufficient. I like that the training curric is stacked and progressive.
My team members all have background as data analysts, so Amp was pretty easy to for them. There was sufficient online training available. We also used the available support documents. The actual rollout went well. We did significant testing beforehand. We did a phased rollout, with partial silent rollout (part of OCM's plan) for the smallest line of business. THe silent one was "silent" b/c it was done without fanfare or public notices ... it was just a "we're doing some things, it wont impact your work or workday
Amplitude Analytics provides much more granular data than Google Analytics and gives you much more flexibility in how you can segment and splice the data. It also provides the ability to create closed funnels, which I have yet to find out how to do in Google Analytics. Amplitude has a very similar interface to Mixpanel, with a few handy additions, like the ability to name and categorize your events.
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
Like all the other grades, it was mostly an easy implementation ... we have experience people, the rollout in general is well planned, and the vendor was very supportive
We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
