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As of Jan 2020, these 48 SaaS companies are the largest in the Big Data Software space.

The Top Big Data Software SaaS Companies

This list tracks the largest private B2B Big Data Software SaaS companies by revenue. In total, this list features 48 companies with combined revenues of $351.7M.

These companies have raised a total of $304.4M. Together, these Big Data Software saas companies serve 33K customers and employ over 6K on their teams.

Divider

Highlights

02
ACLS
ACL Services

Big Data Software

ACL Services is an enterprise governance software powered by data automation for audit, compliance, and risk management.

$40M
$50M
14K
808
1987
Canada
03
I
Idwall

Big Data Software

Idwall develops software to help small and medium-sized businesses in customer credentialing process.

$24M
$52M
300
181
2016
Brazil
04
P
Privacera

Big Data Software

Privacera is a SaaS-based data security and governance platform that offers data sharing without compromising regulatory compliance.

$12M
$50M
500
147
2016
United States
05
XTARGET
X TARGET

Big Data Software

X TARGET is a DaaS data technology service provider in the retail industry.

$11M
$3M
-
145
2014
China
06
ULT
UpLexis Tecnologia

Big Data Software

UpLexis Tecnologia specializes in emerging technologies for analyzing and interpreting large volumes of data.

$8M
-
-
223
2005
Brazil
07
CI
CloudIn

Big Data Software

CloudIn is an international technology company that provides IaaS- and PaaS-based cloud services.

$7M
$10M
-
98
2015
China
08
S
Syapse

Big Data Software

Syapse provides real-world evidence through SaaS to health systems and life sciences companies to improve the outcomes of cancer patients.

$7M
$30M
-
116
2008
United States
09
C
Clickagy

Big Data Software

Clickagy is a filter overlaid on the world's digital activity to better identify, understand, and reach specific audiences. By collecting real-time, granular data directly from the source – observed online behaviors of 91% of accessible devices – Clickagy is able to analyze anonymous user data to derive interests and psychographics.

$6M
-
5K
12
2012
United States
10
Z
Zhiziyun

Big Data Software

Zhiziyun is a big data technology service provider that provides efficient SaaS platforms and privatized customized services.

$6M
$2M
-
96
2012
China
1 - 10 of 48Next

What are the fastest growing companies doing?


83 of the fastest growing companies that also have the most revenue have a clear expansion revenue strategy. On average, sales reps are selling plans where starting contract value is $4,606.

Those same companies employ 1,678 sales reps that carry a quota. The most common compensation plan used by these companies is a 1:5 ratio of sales rep on target earnings (OTE) to quota. Meaning if a rep can earn $200k in base and commissions, quota target for that year is set at 5x, or $1m in new ARR closed.

If you’re going to build a high growth SaaS company, you need to figure out how to scale with quota carrying sales reps.

Which CEO’s are the most efficient capital allocators?


We can measure this a variety of ways. Which company has the most revenue per employee? What about dollars in revenue compared to dollars raised? What about time, which founder went from $0 to $10m the fastest?

Looking deeper at dollars in revenue compared to dollars raised, bootstrappers take the cake because they self fund (denominator zero). When we look at companies that have raised at least $1m, Actito is the clear winner generating $21m in revenue, growing 100% yoy, on just 1m raised ($.05 dollars raised for every $1 of revenue).

Omnisend comes in a close second with $.08 dollars raised for every dollar of revenue. Doing $19m as of December 2020. Proposify gets honorable mention with $0.46 dollars raised (3.25m) for every dollar of revenue ($7m).

The worst performers here are companies like YayPay with $3.68 dollars raised ($14m) per dollar of revenue ($3.8m). Many of the worst performers just did a round of funding and haven’t had a chance to deploy to drive growth yet. That makes this data less valuable but still illustrative.