Google BigQuery vs. Amazon Redshift vs. Salesforce Agentforce Sales

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).

Incentivized

If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)

Incentivized

Obviously, for any business, there are two main areas to focus on — the sales path and the service path. Sales Cloud wouldn’t be suited for a company that’s primarily into support services. For those kinds of companies, Salesforce has a different product — Service Cloud. So, for anyone in the support or service space, Sales Cloud isn’t the right fit.

Incentivized

• Realtime integration with Google Sheets.
• 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.

Incentivized

• [Amazon] Redshift has Distribution Keys. If you correctly define them on your tables, it improves Query performance. For instance, we can define Mapping/Meta-data tables with Distribution-All Key, so that it gets replicated across all the nodes, for fast joins and fast query results.
• [Amazon] Redshift has Sort Keys. If you correctly define them on your tables along with above Distribution Keys, it further improves your Query performance. It also has Composite Sort Keys and Interleaved Sort Keys, to support various use cases
• [Amazon] Redshift is forked out of PostgreSQL DB, and then AWS added "MPP" (Massively Parallel Processing) and "Column Oriented" concepts to it, to make it a powerful data store.
• [Amazon] Redshift has "Analyze" operation that could be performed on tables, which will update the stats of the table in leader node. This is sort of a ledger about which data is stored in which node and which partition with in a node. Up to date stats improves Query performance.

Incentivized

• The customizations - We have an organization that operates differently from most companies, so we’ve had to implement quite a few customizations — and Salesforce allows us to do that quite quickly. Most of the time, delays come from dependencies on other internal parties rather than the system itself.
• From my perspective as a consultant, one of the biggest advantages is that everything is in Salesforce — all the details, all in one place. The ability to customize it easily is a big plus; there’s really a lot you can do with it.

Incentivized

• 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.

Incentivized

• We've experienced some problems with hanging queries on Redshift Spectrum/external tables. We've had to roll back to and old version of Redshift while we wait for AWS to provide a patch.
• Redshift's dialect is most similar to that of PostgreSQL 8. It lacks many modern features and data types.
• Constraints are not enforced. We must rely on other means to verify the integrity of transformed tables.

Incentivized

• We still need to include the production part. We started using Salesforce to sell the seeds — our inventory is in SAP — and from there we handle sales and track the process of planting, harvesting, selling, and then collecting payments. But we don’t yet manage the earlier production processes, like production planning. We handle allocation, but not full production planning, and that’s an area where we still have room for improvement.

Incentivized

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.

Incentivized

There are days when I wish we hadn't switched, but I know that if we put in the time, we will get to where we want to be with the software and that it has many more capabilities than anything else we looked at. However, the amount of time and onboarding we need to do is also far greater than we realized/were told when we originally bought the product. They told us we should hire onboarding support, but at the end, after we had already reached our budget maximum for this, so it's been slower than we had hoped.

Incentivized

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.

Incentivized

Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.

Incentivized

Because I think it could be easier. We have different standards today since we’re used to interacting with consumer apps like Starbucks, where all you do is scan your card. Then, when you use Sales Cloud, there are still a lot of manual inputs. So my mission with AI is really about figuring out how to make that easier.

Incentivized

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.

Incentivized

Salesforce is always available securely from any internet-capable device anywhere in the world, UNLESS you choose to set security measures so that ONLY trusted IP ranges may access the system at certain times of the day. It's all about choice and flexibility with Salesforce products.

Incentivized

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.

Incentivized

Salesforce performance in general is excellent. "The cloud infrastructure beneath Force.com has been fine-tuned over the past 10 years. It powers nearly 100,000+ businesses running more than 185,000 applications that 3 million users count on every day."
Points per Salesforce -
1) Multitenant kernel - With a multitenant platform, each business that uses the app doesn’t have its own copy. Instead, all businesses share a single copy and then customize it for their specific needs.
2) ISO 27001 certified security - You can’t compromise when it comes to enterprise-level security. Force.com is road-tested and trusted by nearly 100,000+ companies, including many of the world’s most security-conscious organizations, such as banks and health care providers.
3) Proven reliability - All Force.com apps run on world-class data centers with backup, failover, and disaster-recovery facilities. Force.com has had a proven 99.9 percent uptime record for years.
4) Proven, real-time scalability - Force.com is used by many of the world's largest enterprises, including Cisco, Japan Post Network, and Symantec. Applications can automatically scale from a few users to millions of page views, as needed.
5) Real-time query optimizer - You need fast access to your data. The Force.com query optimizer delivers under 300ms response time, at a massive scale.
6) Real-time transparent system status - You can always see real-time system performance, availability, and security information at trust.salesforce.com.
7) Real-time upgrades - Unlike traditional software platforms, our upgrades never break your customizations, code, or integrations. We upgrade the platform for you 3 to 4 times each year. As a result, you’re always on the latest version, with access to the latest features, performance, and security enhancements.
8) Real-time sandbox environments - With a single click, you can create copies of your applications, configuration, and data in separate environments for development, testing, and training.
9) Three global production data centers and disaster recovery - Force.com runs on three geographically dispersed, mirrored data centers with built-in replication, disaster recovery, a redundant network backbone, and no single points of failure

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.

Incentivized

The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support

Incentivized

The overall support has been good. More and more features are being released quite frequently. Very small features are also making big difference in how the tool can be adapted and used better. If there is anything we need or are stuck, the support team sets up a call and helps in resolving the issue/provides workarounds.

I attended two training sessions. I would rate them a 4 as an advanced user. It was very basic – great for someone new – would give 8+ for new person.

I had 3 years of experience at the time. I skipped basic and went onto advanced and still not helpful. A lot of it was best practices that didn’t feel relevant for our business

I have gone through multiple. The content that’s delivered is quite basic – I wish they had more advanced training.

We are grandfathered into premium support plus training. We get unlimited access to instructor led and online training for free. We have taken advantage of this

Just from an organizational standpoint - we standardized our data prior to moving to Salesforce. But we essentially standardized it wrong. That's created a big disgusting mess for us know that I'll have to deal with as the Admin. Be sure you think through use cases prior to doing something like that - seek outside opinions on how the data will work best, especially depending on what else you're going to integrate with Salesforce.

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.

Incentivized

Than Vertica: Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS).
Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again.
Than Hive: Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.

Incentivized

So I've evaluated, implemented Microsoft Dynamics in the past. I've used Oracle CRM solutions. I've used Daylight, which is a very niche CRM system the last couple of years. And I've evaluated a variety from Legacy Microsoft Ones to Zoho and Sugar when making implementation decisions at other companies. But usually I've gone with Salesforce. I'd say it's better than most. The only one that I generally prefer, and last time I chose an implementation from scratch, I did Microsoft Dynamics. And the reason is for small mid-size organization, Microsoft Dynamics, if you already have Microsoft Office products, it's much better integrated to all of the Excel, Word, OneNote, Outlook email than what you get from Salesforce. And so that's the only one that if someone's a Microsoft organization and small sized company, it'll save a lot of integration things, a lot of security, a lot of login and access and IT management by just sticking within the Microsoft ecosystem. But outside of that, if you don't use Microsoft or if you're a large organization or have other needs that you want, Salesforce I'd say is better than all of the other CRM offerings out there. It's the easiest to use and the most robust and the most vendors and products for the ecosystem.

Incentivized

None so far. Very satisfied with the transparency on contract terms and pricing model.

Redshift is relatively cheaper tool but since the pricing is dynamic, there is always a risk of exceeding the cost. Since most of our team is using it as self serve and there is no continuous tracking by a dedicated team, it really needs time & effort on analyst's side to know how much it is going to cost.

Incentivized

Salesforce is the most widely used CRM system. Professionalism tends to increase when things go wrong for market leaders. Salesforce considers us as users because they own the market. Having all of our data in one place and all of our teams working within Salesforce. Anyone who uses Salesforce is impacted by it, even if they don't.

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.

Incentivized

It's very scalable as it has a ton of features (but you do need an admin who understands how to leverage these features). Because of the various features, we've also needed to host onboarding sessions with our users so that they can familiarize themselves with the platform, which isn't always super user-friendly or intuitive.

Incentivized

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.

Using Salesforce.com has made my daily routines more efficient and simplified the manual tasks I had to perform independently. I can now access data from any device, online or offline, and provide better guidance to my team about the forecasts provided by the built-in artificial intelligence (AI). A chat with a Salesforce support specialist would be great. The knowledge base has a community forum where Salesforce users can ask questions and learn more about the product.

• 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.

Incentivized

• Our company is moving to the AWS infrastructure, and in this context moving the warehouse environments to Redshift sounds logical regardless of the cost.
• Development organizations have to operate in the Dev/Ops mode where they build and support their apps at the same time.
• Hard to estimate the overall ROI of moving to Redshift from my position. However, running Redshift seems to be inexpensive compared to all the licensing and hardware costs we had on our RDBMS platform before Redshift.

Incentivized

• It allows me to keep a close eye on all of my performance metrics through the Dashboard Reporting, ie what my sales pipeline looks like, how much it's changed in the last 60 days, new opportunities created in the last 7 days, # of emails sent for the week, etc. The ease of the design and output make it really easy to check my progress throughout the day to find where I have holes and am falling short on my personal and work goals. It's resulted in greater transparency with my Mgmt Team and shorter 1-on-1 mtgs with my boss as he can see exactly where I am at all times (to be fair, I'm a senior sales rep, so he pretty much lets me do my job completely unfettered), but it does prove that I am continually producing which recently resulted in a raise I didn't even ask for.
• The SF repository is so detailed that I don't have to spend tons of time finding frequently used websites attached to a client or see what all interactions with the company look like. Even though I don't use SF for my bulk emails and email sequences, SF provides me with an email to use in the bcc of these emails which links everything back to SF. I find that extremely helpful. This really impacts my efficiency and I can honestly say that once I started using all the functionality of data management, it saved me about 20% of my time/week that I could then allocate towards other revenue-generating tasks like prospecting and account management. The more time I have for those, the better. My year-over-year on accounts 1 year and older just grew by 17% this last year.

Incentivized