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That is, until you’ve got a major enterprise deal close to the finish line. At Secureframe , we help companies get enterprise ready by streamlining SOC 2 compliance and get them ready within weeks, rather than months. . Security, besides having a password that isn’t “password123”, is probably not a major priority. .
Ron and his team tapped into their VC network, particularly a16z, to land early enterprise deals. And we found a lot of our big enterprise customers through that channel early days. But Ron quickly saw that bigger dollars were in the enterprise. They set up meetings with Fortune 500 CIOs. A common mistake founders make?
So follow AWS, Azure and Google Cloud. Let’s look a whole level up to the real canaries-in-the-coalmine: AWS, Azure and Google Cloud. And AWS grew 37% at a $74B run-rate , down a bit from 39% the prior quarter but still adding an insane amount of new revenue. If they stumble, we’re in for a rough patch.
Shopify , Datadog, Crowdstrike , Google Cloud-Azure-AWS, Snowflake , etc. In fact, Gartner predicts enterprise software spend will cross $1 Trillion Dollars (!) At the end of the day, 2024 may well be a year of Divergent Headlines. SaaS and Cloud growth overall will remain strong. for the first time in 2024!
Focusing on smaller developers, in some ways it’s been a bit overshadowed by AWS, Azure, and Google Cloud. DigitialOcean doesn’t want to take AWS, Azure and Google on in the enterprise and doesn’t really try. Even as the Big Guys went more and more enterprise. Wow what a story!!
They each have some of the largest cloud businesses in the world in AWS, Azure and Google Cloud respectively. Multiples shown below are calculated by taking the Enterprise Value (market cap + debt - cash) / NTM revenue. Overall, there was weakness across the board. Not the best start to cloud software earnings season!
Secureframe helps companies get enterprise ready by streamlining SOC 2, ISO 27001, GDPR, CCPA, PCI DSS and HIPAA compliance. Secureframe allows companies to get compliant within weeks, rather than months and monitors 100+ services, including AWS, GCP, and Azure.
At SaaStr AI Day , Mike Tamir, Head of AI at Shopify, and Rudina Seseri, founder and Managing Partner at Glasswing Ventures, level-set about where we are in the cycle for Enterprises adopting AI and the critical work being done at Shopify to leverage AI and solve real problems. The future of Enterprise is “Ambient AI.”
The platform automates the provisioning of your application to the cloud (AWS, GCP, Azure), integrating cloud ops, DevOps, and security/compliance with 24×7 monitoring and support. SafeBase enables sales and security teams to efficiently collaborate and close enterprise deals faster.
Secureframe helps companies get enterprise ready by streamlining SOC 2, ISO 27001, GDPR, CCPA, PCI DSS and HIPAA compliance. Secureframe allows companies to get compliant within weeks, rather than months and monitors 100+ services, including AWS, GCP, and Azure.
And it’s one of the three large cloud vendors that we all know: Microsoft, AWS, and Google. Azure’s marketplace has over 4 million monthly visitors. AWS’s marketplace has seen 1.5 Rico Mallozzi: So marketplaces are fundamentally changing, go to market motions for a lot of enterprise technology companies.
Enterprises are spending an additional $20B on SaaS each year. That’s $20B more budget than last year, just for enterprises alone. The SaaS companies with $1B in ARR have 1% of all total enterprise spend. E.g., if Slack at $1B is 50% enterprise, that probably means 0.5% Go grab your piece. Go make it happen.
Reprise provides a no-code, enterprise-ready platform that gives teams the power to control the narrative of their demos and deliver custom product experiences—without developer involvement. Secureframe helps companies get enterprise ready by streamlining SOC 2, ISO 27001, PCI DSS and HIPAA compliance.
Coming out of that, every company from the largest enterprise to the smallest startup started thinking very critically about cost optimizations. Multiples shown below are calculated by taking the Enterprise Value (market cap + debt - cash) / NTM revenue. So why was it stronger than normal last year? Where was wasted spend with low ROI.
In the cloud, AWS, Azure, & GCP have created about as much market cap as all the top 100 B2B & B2C publics built on cloud (Netflix, ServiceNow, AirBnb, etc). Enterprise readiness will be an essential : ensuring buyers are safe from legal & compliance risks. Layer : application, platform, or infrastructure?
Subscribe now Cloud Giants Report Q3 ‘23 Not a great signal for software this week from the Cloud Giants (AWS, Azure and Google Cloud)…After Q2 (3 months ago), the tone from the Cloud Giants around optimizations was largely: optimizations have started to ease, and net new workloads have picked up. Staggering scale already.
We now have results from the three hypersclaers (AWS / Azure / GCP). The most notable change in tone was Andy Jassy talking about AWS. Multiples shown below are calculated by taking the Enterprise Value (market cap + debt - cash) / NTM revenue. ” Full quote below: “We're seeing a few trends right now.
Snowflake announced earnings yesterday, echoing the strength within software companies more broadly & underscoring the shift in enterprise buyer behavior to normal after three quarters of extensive cost cuts. “Yes, we actually saw quite a bit of energy coming from the Azure platform this quarter.
Amazon on AWS : “…customers are continuing to shift their focus towards driving innovation and bringing new workloads to the cloud. ” Microsoft on Azure : “And I think last quarter, we said one, we are going to continue to have these cycles where people will build new workloads. Follow along to stay up to date!
The role of AWS, Azure, and Google Cloud Marketplace is becoming increasingly important. “45% This need for ease is even more true for enterprises. The cliche that enterprises have more money than time certainly plays out here. . “88% Is this software easy to use? Is it easy to implement? Will I see value quickly?
But enterprise buying went on a tear. That $200b+ of additional Cloud and SaaS spend fueled 50+ Cloud unicorns and massive growth in AWS, Azure, etc. There were dips in 2016 and otherwise. It’s still accelerating.
Cloud Downgrades This week UBS came out with a couple research reports citing concerns in AWS / Azure growth. This brings me back to AWS / Azure downgrades. Multiples shown below are calculated by taking the Enterprise Value (market cap + debt - cash) / NTM revenue. Follow along to stay up to date!
Hyperscaler Preview Next week Amazon, Microsoft and Google report earnings and we’ll see Q3 data for AWS, Azure and Google Cloud. However, it’s important to keep in mind that while hype and expectations are quite high around AI, true enterprise buying cycles typically lag. Overall Stats: Overall Median: 5.7x
Hyperscalers Report Quarterly Earnings This week we saw AWS (Amazon), GCP (Google) and Azure (Microsoft) report earnings. Overall, it wasn’t pretty… AWS grew 28% when expectations were 30-31%. At the same time, Azure came in below expectations. Follow along to stay up to date!
AWS (Amazon), Azure (Microsoft), and Google Cloud (Google) all reported this week. Azure reported on Tuesday and gave us that glimmer of hope. Then AWS appeared to add fuel to that hope before giving us a huge rug pull. Azure came in at 31% (constant currency). They then guided to 26-27% Azure growth in Q2.
” These are two quotes about AWS on the Amazon earnings call. AWS grew 16% in Q1, but called out growth in April (first month of Q2) was 11%. You can see more detail about their net new ARR added each quarter below Azure Growth came in at 27%, and guided to 25-26% growth for Q3. Overall Stats: Overall Median: 6.4x
Cloud Giants Report Q2 We also got the Q2 quarters from AWS / Azure / GCP this week! Multiples shown below are calculated by taking the Enterprise Value (market cap + debt - cash) / NTM revenue. A lot of companies report next week, we’ll see if they’re able to quell any fears! Overall Stats: Overall Median: 5.2x
Subscribe now Foundation Models Are to AI what S3 was to the Public Cloud Many people look at 2006 as the birth of the public cloud - the year Amazon launched AWS. Microsoft launched Azure in 2010, and Google launched GCP to the public in 2011 (they launched a preview of Google App Engine in 2008, but made it publicly available in 2011).
Next week we get all 3 hyperscalers reporting (AWS from Amazon, Azure from Microsoft, and GCP from Google). Let’s double click on Azure. On AWS, in their Q4 earnings call they said AWS was growing “mid teens” in January (down from 20% in Q4). The Q4 ‘22 growth rate was 38% YoY.
Usage on Snowflake is driven by queries run on Snowflake Azure: Neutral Tone With Strength in AI Overall I’d characterize Azure’s quarter as a net positive. They guided to 26-27% growth in Azure in Q2 (with 1% coming from AI). Their consumption is driven by usage of applications built on top of Mongo.
AI = Data + Compute I’ll continue beating this drum, but we got two great quotes from Azure and AWS this week. ” Then at AWS Summit they called out “Your data is your differentiator when it comes to Generative AI.” AWS reports next week. ” Data is more important than ever! Bucketed by Growth.
All 3 (AWS, Azure, GCP) saw positive reacceleration Quarterly Reports Summary Top 10 EV / NTM Revenue Multiples Top 10 Weekly Share Price Movement Update on Multiples SaaS businesses are generally valued on a multiple of their revenue - in most cases the projected revenue for the next 12 months. Overall Stats: Overall Median: 5.7x
Ali Ghodsi, CEO and cofounder of Databricks, and Ben Horowitz, cofounder of a16z, explain the data wars happening inside and outside enterprises and how they could impact the evolution of LLMs. [00:38] 00:38] Why is it so hard for enterprise to adopt AI? [03:08] But we haven’t seen anybody with any traction in enterprise.
The traditional clouds (AWS, GCP, and Azure) are getting dated. They continue to be the standard for the vast majority of cloud workloads, of course, but they are built around a set of operational practices that were more relevant a decade ago.
Enterprise software businesses strive for 90-95% gross retention (generally the percent of revenue that sticks with you vs churns altogether), with net expansion in the 120%+ range (the aggregate change in expansion - contraction - churned revenue). .” It’s probably better described as re-occurring vs recurring.
This can lead to an airpocket of valuation as companies transition to a different primary valuation metric Outside of the hypserscalers (Azure, AWS, GCP) who have uniquely benefited from AI revenue (mainly selling compute), everyone else has largely struggled. Coming in to Q1 there was broader optimism. Q4’s were generally good!
Hyperscalers (AWS, Azure, GCP as companies look for cloud GPUs who aren’t building out their own data centers) Infra (Data layer, orchestration, monitoring, ops, etc) Durable Applications We’ve clearly well underway of the first 3 layers monetizing. Even a DCF is riddled with long term assumptions. Top 5 Median: 14.5x
In the short term, enjoy the ride as the chase continues 😊 Kind of related to all of this - we now have seen the Q4’s from AWS, Azure and Google Cloud. Multiples shown below are calculated by taking the Enterprise Value (market cap + debt - cash) / NTM revenue. Lots of deceleration in growth. Top 5 Median: 14.5x
If next quarter we get similar commentary that Azure gave us this quarter (“still a couple quarters away” without any specific guidance), then we may see market loose a little patience. The hyperscalers (AWS, Azure, GCP) are seeing some uptick, but this is largely from selling compute (ie cloud GPUs).
It can also take a relatively long time to complete, particularly for large enterprises with far-flung operations. Also on InfoWorld: VMware Cloud on AWS? Because these applications are generally so well entrenched within organizations and among end users, migrating to the cloud can be a cultural and technical challenge.
Related: Enterprise SaaS Architecture – The How. Going the Amazon Web Services (AWS) route? Your SaaS tech stack should ideally be powered by Python, React, and AWS programming combo. With Microsoft Azure, you have MySQL or PostgreSQL, which can be procured from the Azure portal. instead of Python.
As Frank Slootman (Snowflake CEO) said, “Enterprises are also realizing that they cannot have an AI strategy without a data strategy to base it on.” Typical data lake storage solutions include AWS S3, Azure Data Lake Storage (ADLS), Google Cloud Storage (GCS) or Hadoop Distributed File System (HDFS).
Also on InfoWorld: AWS vs. Azure vs. Google Cloud: Which free tier is best? ]. Some enterprises have not yet used open source on premises, not to mention cloud. Cloud providers charge for usage, either by time or other resource-units consumed. Indeed, it’s half or more of the cloud computing bills I’ve seen recently.
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