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Amazon DynamoDB VS Google Cloud Bigtable_
As of 30 October 2026, Google Cloud Bigtable is named by 109 companies and Amazon DynamoDB by 1,440; Amazon DynamoDB skews to companies under 200 people (46% vs 38%), Google Cloud Bigtable to companies over 1,000 (31% vs 28%).
As of 30 October 2026 · refreshed daily · counts move as websites, DNS and career sites are re-read.
The website-and-DNS footprint is not comparable between a marketing suite and a CRM: Amazon DynamoDB's script and mail records show on hundreds of thousands of small sites, Google Cloud Bigtable rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Amazon DynamoDB: 2–200 employees
- 46%
- Google Cloud Bigtable: 2–200 employees
- 38%
- Amazon DynamoDB: 1,000+ employees
- 28%
- Google Cloud Bigtable: 1,000+ employees
- 31%
- Postings per company, 90 days
- 2.9 · 3.5
- Website or DNS footprint
- 0 · 0
Who chooses which
Share of each tool's companies in every segment. "Leans" marks a gap of more than two points.
| Segment | Amazon DynamoDB | share | Google Cloud Bigtable | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 20 | 1% | 2 | 2% | even |
| 2-10 employees | 95 | 7% | 5 | 5% | Amazon DynamoDB |
| 11-50 employees | 225 | 16% | 11 | 10% | Amazon DynamoDB |
| 51-200 employees | 339 | 24% | 25 | 23% | even |
| 201-500 employees | 218 | 15% | 16 | 15% | even |
| 501-1000 employees | 140 | 10% | 16 | 15% | Google Cloud Bigtable |
| 1001-5000 employees | 185 | 13% | 15 | 14% | even |
| 5001-10000 employees | 65 | 5% | 5 | 5% | even |
| 10,001+ employees | 153 | 11% | 14 | 13% | Google Cloud Bigtable |
| Segment | Amazon DynamoDB | share | Google Cloud Bigtable | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 845 | 59% | 66 | 61% | even |
| Business & finance services | 268 | 19% | 22 | 20% | even |
| Manufacturing & industry | 82 | 6% | 6 | 6% | even |
| Media & content | 57 | 4% | 2 | 2% | Amazon DynamoDB |
| Consumer services & leisure | 38 | 3% | 4 | 4% | even |
| Commerce & trade | 29 | 2% | 2 | 2% | even |
| Utilities & infrastructure | 29 | 2% | 1 | 1% | even |
| Health care | 23 | 2% | 1 | 1% | even |
| Transport, logistics & rental | 19 | 1% | – | – | outside top 12 |
| Automotive | 15 | 1% | 1 | 1% | even |
| Public, community & associations | 15 | 1% | 4 | 4% | Google Cloud Bigtable |
| Property & construction | 12 | 1% | – | – | outside top 12 |
| Segment | Amazon DynamoDB | share | Google Cloud Bigtable | share | Leans |
|---|---|---|---|---|---|
| United States | 936 | 65% | 83 | 76% | Google Cloud Bigtable |
| United Kingdom | 113 | 8% | 5 | 5% | Amazon DynamoDB |
| Germany | 53 | 4% | 2 | 2% | even |
| India | 46 | 3% | 1 | 1% | Amazon DynamoDB |
| Canada | 40 | 3% | 4 | 4% | even |
| France | 26 | 2% | 3 | 3% | even |
| Brazil | 24 | 2% | – | – | outside top 12 |
| Australia | 18 | 1% | 2 | 2% | even |
| Japan | 18 | 1% | – | – | outside top 12 |
| Singapore | 16 | 1% | 2 | 2% | even |
| Italy | 15 | 1% | – | – | outside top 12 |
| Poland | 13 | 1% | 2 | 2% | even |
| Spain | – | – | 3 | 3% | outside top 12 |
| Colombia | – | – | 1 | 1% | outside top 12 |
| Estonia | – | – | 1 | 1% | outside top 12 |
| Segment | Amazon DynamoDB | share | Google Cloud Bigtable | share | Leans |
|---|---|---|---|---|---|
| Software engineering | 3,526 | 61% | 253 | 50% | Amazon DynamoDB |
| Data & AI | 939 | 16% | 121 | 24% | Google Cloud Bigtable |
| IT operations & business systems | 486 | 8% | 50 | 10% | even |
| Customer service & success | 79 | 1% | 4 | 1% | even |
| Product, program & project management | 54 | 1% | 7 | 1% | even |
| Engineering (non-software) | 39 | 1% | 6 | 1% | even |
| Sales | 27 | 0% | 5 | 1% | even |
| construction and civil | 9 | 0% | – | – | outside top 12 |
| Design & UX | 7 | 0% | – | – | outside top 12 |
| Unclassified | 7 | 0% | – | – | outside top 12 |
| Legal, compliance & risk | 5 | 0% | – | – | outside top 12 |
| Marketing & communications | 4 | 0% | – | – | outside top 12 |
| Human resources | – | – | 2 | 0% | outside top 12 |
| arts media and entertainment | – | – | 1 | 0% | outside top 12 |
| Education & training | – | – | 1 | 0% | outside top 12 |
| General management & consulting | – | – | 1 | 0% | outside top 12 |
The companies behind each column
Companies using Amazon DynamoDB →
Companies using Google Cloud Bigtable →
nosql document wide column ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Google Cloud Bigtable is named by 109 companies in job postings and Amazon DynamoDB by 1,440; 0 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/amazon-dynamodb-vs-google-cloud-bigtable)
Read from the source, not self-reported
Every number on this page can be traced to a page we crawled or a posting we read. Full methodology →
- Job postingsRead hourly from career sites. A tool counts when the employer's own text names it as the team's system; both tools can count for one company.
- Website and DNSScripts and embeds on the company's pages, plus SPF, DKIM, MX and CNAME records of its domain that point at the vendor.
- SegmentsCountry, size and industry from the company profile built from its website.
- Not a reviewNo ratings, prices or feature claims. For those, read the vendors.
Amazon DynamoDB vs Google Cloud Bigtable: questions
Which is more used, Amazon DynamoDB or Google Cloud Bigtable?
By companies naming it in their own job postings, Amazon DynamoDB (1,440) over Google Cloud Bigtable (109). By website-and-DNS footprint, Google Cloud Bigtable (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Amazon DynamoDB?
46% of Amazon DynamoDB companies have 2 to 200 employees, against 38% for Google Cloud Bigtable. 28% of Amazon DynamoDB companies have over 1,000 employees, against 31% for Google Cloud Bigtable.
Do companies run both?
0 companies name both in their postings, usually Amazon DynamoDB in marketing and Google Cloud Bigtable in sales, or during a migration.
Where do these numbers come from?
From the employer's own text in job postings read hourly from career sites, and from scripts found on company websites in our crawl. No vendor data, no surveys.
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