Snowflake (SNOW) Stock News and Forecasts for Dec. 16, 2025: Analyst “Outperform,” Insider Sale Filings, and the Databricks Rivalry

Snowflake Inc. (NYSE: SNOW) stock traded higher on Tuesday, December 16, 2025, as investors weighed fresh Wall Street commentary on the company’s AI monetization path, a new wave of Rule 144 insider-sale filings, and a major competitive signal from private-market rival Databricks. SNOW last traded around $218.80, up about 1.6% on the session, after touching an intraday high near $219.92.

The big picture: Snowflake is still trying to convert its role as a cloud data-warehouse leader into a broader “data + AI platform” narrative—while proving it can do so without sacrificing growth durability or margins. That tension is exactly what dominated today’s analyst notes.

What moved Snowflake stock on Dec. 16, 2025

1) Raymond James launches “Outperform,” but trims target to $250

A key headline Tuesday was a new Outperform rating from Raymond James that frames Snowflake as being at an “inflection point”—evolving from a cloud data warehouse into a broader data-and-AI platform. The firm trimmed its price target to $250 from $274, outlining five core debates it believes will drive SNOW over the coming years (AI monetization, platform convergence, consumption elasticity, open formats/interoperability, and hyperscaler dynamics). ^[1]

2) TD Cowen reiterates “Buy,” keeps a notably low $134 target

TD Cowen also reaffirmed a Buy rating following investor meetings with management held December 15, but kept a $134 price target—a figure that sits well below SNOW’s current trading level. In its commentary, TD Cowen pointed to execution improvements, reduced balance-sheet “tail risks,” and a longer-term transition toward a more durable revenue/earnings model. ^[2]

That target is an outlier versus most published analyst targets and likely reflects firm-specific modeling assumptions rather than a consensus view—especially given Snowflake’s sharp 2025 run and the sector’s premium valuations.

3) Mizuho spotlights Snowflake among “top enterprise software” ideas for 2026

In the “software winners for 2026” conversation, Mizuho named Snowflake alongside major enterprise names as part of its favored list as software-sector momentum builds. ^[3]

4) Competitive pressure back in focus: Databricks’ $134B valuation headline

Adding fuel to the “data platform arms race” narrative, Databricks announced a Series L funding round of more than $4 billion valuing the company at $134 billion, highlighting strong investor appetite for enterprise AI/data infrastructure even outside public markets. Reuters reported Databricks said it had reached a $4.8 billion revenue run rate and planned to invest in AI-driven applications, R&D, and acquisitions. ^[4]
Databricks’ own statement likewise emphasized the $134B valuation and the $4.8B run-rate milestone. ^[5]

For Snowflake shareholders, this matters less as a direct “one-day catalyst” and more as a reminder: the competitive set is not standing still, and private players can raise huge sums to fund aggressive product expansion.

Insider sale filings hit the tape: what Rule 144 notices are (and aren’t)

Several Form 144 filings circulated on December 16, which can sometimes spook short-term traders even when the amounts are small.

A Refinitiv report noted VP Christian Kleinerman filed to sell 2,975 shares, with the approximate sale date listed as 12/16/25, and the filing referenced a prearranged 10b5-1 plan. ^[6]
Separately, a Rule 144 notice indicated Benoit Dageville filed regarding a proposed sale of 1,912 shares, tied to restricted stock vesting dated 12/15/2025, with an approximate sale date of 12/16/2025. ^[7]
Another filing indicated Frank Slootman filed a notice covering a proposed sale of 7,728 shares, also tied to restricted stock vesting and listing 12/16/2025 as the approximate sale date. ^[8]

Rule 144 filings are not the same as “big insider dumping.” They are notices of proposed sales of restricted or control securities, and they often coincide with routine vesting schedules and/or 10b5-1 trading plans. Still, in a stock where sentiment can swing on valuation and growth expectations, even routine filings can add noise.

The operating backdrop: what Snowflake last reported and guided

Most of today’s analyst debate traces back to Snowflake’s fiscal Q3 2026 results (quarter ended October 31, 2025). In that report, Snowflake posted:

Product revenue of about $1.16 billion, up 29% year over year
Total revenue of about $1.21 billion (also 29% growth)
Net revenue retention rate of 125%
Remaining performance obligations (RPO) of $7.88 billion, up 37% year over year
688 customers with trailing 12-month product revenue > $1 million
766 Forbes Global 2000 customers ^[9]

Guidance that sparked a debate about “AI-era software margins”

For fiscal Q4 2026, Snowflake guided to product revenue of $1.195–$1.200 billion (about 27% growth) and a 7% non-GAAP operating margin. For the full year, Snowflake guided to product revenue of about $4.446 billion (about 28% growth) and a 9% non-GAAP operating margin. ^[10]

The market’s pushback after earnings wasn’t about missing estimates; it was about whether Snowflake can keep growth above “investor ambition” levels while funding AI initiatives. Reuters highlighted that while guidance topped consensus, it still fell short of some investors’ hopes for growth above 30%, contributing to a notable post-earnings drop at the time. ^[11]
MarketWatch similarly described how a strong quarter still wasn’t enough for investors focused on slowing product-revenue growth and elevated expectations across usage-based software peers. ^[12]

The 5 debates analysts say will decide Snowflake’s next leg

Raymond James’ note is useful because it organizes what many investors are already watching into a checklist. Here’s what those debates mean in plain English—and what to monitor into 2026.

1) AI monetization: “Cool products” vs. measurable consumption

Snowflake has built out AI-facing products and positioning, and Raymond James cited an AI revenue run-rate surpassing $100 million. The question is whether AI features become a repeatable driver of compute consumption, or whether AI remains more of a competitive “table stakes” layer that pressures margins because of GPU and infrastructure costs. ^[13]

What to watch: AI contribution to product growth, compute usage trends, and whether AI workloads expand customer spend rather than shift existing spend.

2) Platform convergence: expanding wallet share as workloads consolidate

Snowflake wants to be the place where structured, semi-structured, unstructured, and transactional workloads live—plus app development via Snowpark and related services. That directly raises competitive overlap with Databricks. ^[14]

What to watch: net revenue retention, workload “attach” rates, and growth in large customers.

3) Consumption elasticity: visibility in a usage-based model

Snowflake’s model can look fantastic in upcycles—and frustrating in “optimization” periods when customers rein in usage. Raymond James flagged this as a continuing debate, and it’s a key reason SNOW can be volatile around guidance. ^[15]

What to watch: RPO trends, free-cash-flow margins, and signals that optimization cycles are ending (or restarting).

4) Open formats and interoperability: adoption tailwind vs. “moat dilution”

By leaning into open data formats (including Apache Iceberg) and tools like Polaris Catalog, Snowflake lowers adoption friction—but potentially reduces lock-in. ^[16]

What to watch: customer acquisition and churn, shifts in the storage vs. compute mix, and whether interoperability drives incremental compute.

5) Hyperscaler dynamics: partner channel or long-term pricing pressure?

Snowflake’s economics remain deeply tied to AWS, Microsoft Azure, and Google Cloud. The opportunity is distribution and scale; the risk is that hyperscalers keep improving their own data/AI stacks. ^[17]

What to watch: vendor mix, operating margin trajectory, and multi-cloud adoption signals.

Snowflake stock forecast: where Wall Street price targets sit now

Even with today’s mixed notes, broader sell-side “street” forecasts still imply upside—though the range is wide:

MarketBeat lists a consensus price target around $275 (with targets spanning roughly $210 to $325, depending on the snapshot). ^[18]
StockAnalysis shows an average price target around $268.51, with a low/high range of $185 to $325. ^[19]
TipRanks lists an average price target around $287, with a much wider displayed low/high range of $170 to $440. ^[20]

Recent post-earnings target moves have skewed higher in parts of the sell-side community—for example, Citizens raised its target to $325 earlier in December while maintaining a positive stance. ^[21]

The key takeaway for readers: targets cluster in the high-$200s, but there are real disagreements on how to value Snowflake’s growth path, especially if AI-era costs compress margins.

Risks that still matter for SNOW investors into 2026

Beyond the day’s headlines, investors keep circling three practical questions:

Can Snowflake sustain premium valuation multiples if growth remains in the high-20% range? Reuters recently noted Snowflake trading at a far higher forward earnings multiple than some software peers, underscoring how sensitive the stock can be to guidance and sentiment shifts. ^[22]
Will AI expand demand or just reprice infrastructure? Partnerships and AI agent initiatives can boost adoption, but GPU-heavy workloads could challenge margin goals. ^[23]
How intense does the competitive spend cycle become? Databricks’ $134B funding headline is a reminder that competitors have large war chests for R&D, GTM, and acquisitions. ^[24]

Bottom line for Dec. 16, 2025

Snowflake stock’s December 16 news cycle wasn’t about a single “make-or-break” event. It was about narrative confirmation:

Analysts are increasingly treating Snowflake as a platform transition story—and debating whether AI becomes a durable revenue accelerator or a margin headwind. ^[25]
Insider-sale filings introduced short-term noise, though the disclosed amounts look consistent with routine, planned activity. ^[26]
Databricks’ mega-round reinforced the idea that the data + AI stack remains a capital-attracting battleground, keeping competition front-and-center for 2026. ^[27]