Compare Akamai Technologies, Inc. (AKAM) vs Manhattan Associates Inc (MANH) Price & Performance
Price performance (Past 24H)
Key statistics
Key statistics
Akamai Technologies, Inc. vs Manhattan Associates Inc — how do they compare? Akamai Technologies, Inc. trades at $122.5 (market cap $16.77B), while Manhattan Associates Inc trades at $192.8 (market cap $11.38B). The key difference: Akamai Technologies, Inc. is the larger of the two by market cap, and Manhattan Associates Inc is trading nearer its 52-week high, Akamai Technologies, Inc. nearer its low. Which is the better fit depends on your goals.
| AKAM | MANH | |
|---|---|---|
Market Cap | $16.77B | $11.38B |
Sector | Technology | Technology |
52-Week High | $161.14 | $220.19 |
52-Week Low | $71.97 | $120.88 |
Enterprise Value | $22.75B | $11.25B |
Aura AI Summary
Signals from Pluang's Aura AI — not financial advice
Aura AI Summary
Signals from Pluang's Aura AI — not financial advice
Akamai Technologies (AKAM) trades at $122.67, up 4.27% with strong earnings momentum after beating Q2 2026 estimates. The stock shows bearish technical signals but maintains solid fundamentals with $4.21B revenue and 57.45% gross margins. Recent analyst upgrades and a $600M cloud contract highlight growth potential in AI and cybersecurity services.
Outlook remains cautiously optimistic with a $150.11 consensus price target offering 22% upside, though margin compression and competitive pressures present risks. Institutional sentiment leans neutral with 49% hold ratings, requiring monitoring of Q3 earnings execution and infrastructure investment returns.
MANH is trading at $192.63, down 1.56% on the day, with a bullish technical outlook supported by moving averages and strong momentum indicators. The company reported robust Q2 2026 earnings, beating EPS estimates with $1.39 versus $1.32 expected, driven by 26% cloud revenue growth. However, valuation ratios remain elevated with a P/E of 55.93 and P/B of 72.26, indicating high investor expectations. Recent news highlights an ongoing legal investigation into fiduciary duties by the Rosen Law Firm, creating a mixed sentiment backdrop.
The outlook for MANH is cautiously optimistic, with a consensus price target of $210.33 offering 9.2% upside potential. Key opportunities include sustained cloud growth and strong profitability metrics like a 96.38% ROE. Risks involve the high valuation, potential legal overhangs from the investigation, and any slowdown in enterprise software demand. Institutional analysts maintain an 80% buy rating, suggesting confidence in execution despite near-term headwinds.
Returns comparison
Trailing returns across standard periods
Returns comparison
Trailing returns across standard periods
Top news
Latest headlines on both assets
Top news
Latest headlines on both assets
About Akamai Technologies, Inc.
Akamai operates a content delivery network, or CDN, which entails locating servers at the edges of networks so its customers, which store content on Akamai servers, can reach their own customers faster, more securely, and with better quality. Akamai has over 325,000 servers distributed over 4,000 points of presence in more than 1,000 cities worldwide. Its customers generally include media companies, which stream video content or make video games available for download, and other enterprises that run interactive or high-traffic websites, such as e-commerce firms and financial institutions. Akamai also has a significant security business, which is integrated with its core web and media businesses to protect its customers from cyberthreats.
Read more on AKAM →About Manhattan Associates Inc
Manhattan Associates, Inc. is a global leader in supply chain and omnichannel commerce software. The company provides a comprehensive suite of cloud-based and on-premise solutions for warehouse management (WMS), transportation management (TMS), and order management (OMS). MANH's technology helps retailers, wholesalers, and manufacturers manage inventory, optimize logistics, and unify the shopping experience across physical and digital channels.
Read more on MANH →
