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Akeneo

Akeneo

Go Back Location: Nantes, France Industry: Enterprise Software

Website Claim
Akeneo is an open source Product Information Management (PIM) system designed for retailers looking for efficient answers to their multichannel needs. The main purpose of a PIM is to be a central repository of all product data of a company. From a technical point of view, a PIM helps to extract and harmonize data, and propagate data to / from different sources. From a functional point of view, a PIM helps to classify, enrich and translate your product informations. Akeneo is : - open source - superconnected - user friendly - made by merchants for merchants
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Rankings powered by: Semrush Rankings SimilarWeb Analytics

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  • Global: 4056 from 66227 0
  • City: Nantes 5 from 29 0
  • Country: France 74 from 1142 0
  • Industry: Enterprise Software 84 from 1258 0

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GO BACK

   Switch to Countries Board Cities Global Ranking of Startup Ecosystem   Go to 2019  
StartupBlink ranks more than 125 countries and 950 cities according to their startup ecosystem strength. Toggle between Countries/Cities ranking, search for a specific location, and download our PDF Ranking Report
2019 Rank
Country id
Population
Change (from 2017)
City Name
Total Score
Quantity Score
Quality Score
Business Score
1
1
9666055
-
San Francisco Bay, United States
262.878
33.37
222.21
7.30
2
1
21045000
-
New York, United States
55.938
3.88
44.76
7.30
3
5
7556900
-
London, United Kingdom
38.421
14.41
16.71
7.30
4
1
3971883
-
Los Angeles Area, United States
34.219
12.99
13.92
7.30
5
1
4771936
+1
Boston Area, United States
33.946
5.47
21.17
7.30
6
25
3098400
+1
Tel Aviv Area, Israel
23.942
2.60
14.04
7.30
7
29
3426354
-2
Berlin, Germany
22.322
3.18
11.84
7.30
8
1
2720546
-
Chicago, United States
18.412
4.86
6.25
7.30
9
1
684451
-
Seattle, United States
18.107
4.16
6.65
7.30
10
2
10381222
+4
Moscow, Russia
17.504
5.83
4.78
6.90
11
13
5104047
+10
Bangalore, India
17.070
3.95
5.82
7.30
12
8
2138551
-2
Paris, France
16.648
2.98
6.37
7.30
13
1
2168316
-1
Austin, United States
16.236
3.82
5.12
7.30
14
24
8336599
+15
Tokyo, Japan
15.764
1.09
7.38
7.30
15
7
2600000
-4
Toronto, Canada
15.732
4.48
3.95
7.30
16
27
741636
+2
Amsterdam, The Netherlands
15.569
1.75
6.52
7.30
17
45
11716620
-4
Beijing, China
15.213
0.93
7.78
6.50
18
13
26454000
+5
New Delhi, India
15.167
3.38
4.48
7.30
19
3
5029711
+6
Sydney, Australia
14.785
2.67
4.82
7.30
20
1
5700990
-4
Atlanta, United States
14.668
2.69
4.68
7.30
21
1
6158824
+12
Miami Area, United States
14.608
3.29
4.02
7.30
22
1
7539711
+16
Dallas-Fort Worth, United States
14.603
2.60
4.70
7.30
23
19
10021295
+8
Sao Paulo, Brazil
14.521
1.87
5.35
7.30
24
18
1515017
-9
Stockholm, Sweden
14.105
1.24
5.57
7.30
25
7
600000
-6
Vancouver, Canada
13.745
2.43
4.02
7.30
26
1
3283665
-6
San Diego, United States
13.698
2.59
3.80
7.30
27
14
1621537
-10
Barcelona, Spain
13.592
2.73
3.57
7.30
28
45
7482500
+7
Hong Kong, China
13.360
1.83
5.03
6.50
29
13
12691836
+3
Mumbai, India
12.900
2.09
3.51
7.30
30
72
10349312
-3
Seoul, South Korea
12.654
0.65
5.10
6.90
31
45
22315474
-9
Shanghai, China
12.488
0.87
5.11
6.50
32
32
5784538
+4
Singapore City, Singapore
12.146
0.45
4.79
6.90
33
14
3255944
-7
Madrid, Spain
12.069
1.98
2.79
7.30
34
43
2900920
+29
Kiev, Ukraine
11.711
1.32
3.10
7.30
35
3
4963349
-5
Melbourne, Australia
11.300
2.25
1.75
7.30
36
46
1488236
+26
Helsinki, Finland
11.245
0.81
3.13
7.30
37
1
682545
+3
Denver, United States
11.108
1.57
2.23
7.30
38
1
6065644
-1
Philadelphia, United States
10.685
1.73
1.65
7.30
39
51
8540121
+121
Jakarta, Indonesia
10.463
0.54
3.02
6.90
40
45
10358381
+12
Shenzhen, China
10.426
0.23
3.70
6.50
41
29
1260391
+23
Munich, Germany
10.388
0.80
2.29
7.30
42
1
4561038
+19
Phoenix, United States
10.356
1.36
1.69
7.30
43
1
2382037
-15
Portland, United States
10.221
1.75
1.17
7.30
44
20
1024027
-3
Dublin, Ireland
10.181
1.10
1.78
7.30
45
1
6133552
-3
Washington DC Area, United States
10.145
1.34
1.51
7.30
46
1
2117103
+48
Raleigh Durham, United States
10.135
0.82
2.01
7.30
47
28
12294193
+46
Mexico City, Mexico
10.059
0.24
2.52
7.30
48
15
13076300
+12
Buenos Aires, Argentina
10.006
1.30
1.41
7.30
49
7
1600000
-15
Montreal, Canada
9.961
1.62
1.04
7.30
50
1
2427024
+27
Charlotte, United States
9.777
0.80
1.68
7.30
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