AWS Pricing Estimator

Use this estimator to understand how Databricks charges for different workloads

1	m4.large	2	8	0.4	0.4	0.4
2	m4.xlarge	4	16	0.75	0.75	0.75
3	m4.2xlarge	8	32	1.5	1.5	1.5
4	m4.4xlarge	16	64	3	3	3
5	m4.10xlarge	40	160	3.86	8	8
6	m4.16xlarge	64	256	3.86	12	12
7	m5.large	2	8	0.35	0.35	0.35
8	m5.xlarge	4	16	0.69	0.69	0.69
9	m5.2xlarge	8	32	1.37	1.37	1.37
10	m5.4xlarge	16	64	2.74	2.74	2.74
11	m5.12xlarge	48	192	3.86	8.23	8.23
12	m5.24xlarge	96	384	3.86	16.46	16.46
13	m5d.large (Beta)	2	8	0.34	0.34	0.34
14	m5d.xlarge (Beta)	4	16	0.69	0.69	0.69
15	m5d.2xlarge (Beta)	8	32	1.37	1.37	1.37
16	m5d.4xlarge (Beta)	16	64	2.74	2.74	2.74
17	m5d.12xlarge (Beta)	48	192	3.86	8.23	8.23
18	m5d.24xlarge (Beta)	96	384	3.86	16.46	16.46
19	m5a.large (Beta)	2	8	0.31	0.31	0.31
20	m5a.xlarge (Beta)	4	16	0.61	0.61	0.61
21	m5a.2xlarge (Beta)	8	32	1.23	1.23	1.23
22	m5a.4xlarge (Beta)	16	64	2.46	2.46	2.46
23	m5a.8xlarge (Beta)	32	128	3.86	4.91	4.91
24	m5a.12xlarge (Beta)	48	192	3.86	7.37	7.37
25	m5a.16xlarge (Beta)	64	256	3.86	9.83	9.83
26	m5a.24xlarge (Beta)	96	384	3.86	14.74	14.74
27	c3.2xlarge (Deprecated)	8	15	1	1	1
28	c3.4xlarge (Deprecated)	16	30	2	2	2
29	c3.8xlarge (Deprecated)	36	60	3.86	4	4
30	c4.2xlarge	8	15	1	1	1
31	c4.4xlarge	16	30	2	2	2
32	c4.8xlarge	36	60	3.86	4	4
33	c5.xlarge	4	8	0.61	0.61	0.61
34	c5.2xlarge	8	16	1.21	1.21	1.21
35	c5.4xlarge	16	32	2.43	2.43	2.43
36	c5.9xlarge	36	72	3.86	5.46	5.46
37	c5.18xlarge	72	144	3.86	10.92	10.92
38	c5d.xlarge	4	8	0.69	0.69	0.69
39	c5d.2xlarge	8	16	1.37	1.37	1.37
40	c5d.4xlarge	16	32	2.74	2.74	2.74
41	c5d.9xlarge	36	72	3.86	5.48	5.48
42	c5d.18xlarge	72	144	3.86	10.96	10.96
43	r3.xlarge	4	30.5	1	1	1
44	r3.2xlarge	8	61	2	2	2
45	r3.4xlarge	16	122	3.86	4	4
46	r3.8xlarge	32	244	3.86	8	8
47	r4.xlarge	4	30.5	1	1	1
48	r4.2xlarge	8	61	2	2	2
49	r4.4xlarge	16	122	3.86	4	4
50	r4.8xlarge	32	244	3.86	8	8
51	r4.16xlarge	64	488	3.86	16	16
52	r5.large	2	16	0.45	0.45	0.45
53	r5.xlarge (Beta)	4	32	0.9	0.9	0.9
54	r5.2xlarge (Beta)	8	64	1.8	1.8	1.8
55	r5.4xlarge (Beta)	16	128	3.6	3.6	3.6
56	r5.8xlarge (Beta)	32	256	3.86	7.2	7.2
57	r5.12xlarge (Beta)	48	384	3.86	10.8	10.8
58	r5.16xlarge (Beta)	64	512	3.86	14.4	14.4
59	r5.24xlarge (Beta)	96	768	3.86	21.6	21.6
60	r5d.large (Beta)	2	16	0.45	0.45	0.45
61	r5d.xlarge (Beta)	4	32	0.9	0.9	0.9
62	r5d.2xlarge (Beta)	8	64	1.8	1.8	1.8
63	r5d.4xlarge (Beta)	16	128	3.6	3.6	3.6
64	r5d.12xlarge (Beta)	48	384	3.86	10.8	10.8
65	r5d.24xlarge (Beta)	96	768	3.86	21.6	21.6
66	r5a.large (Beta)	2	16	0.41	0.41	0.41
67	r5a.xlarge (Beta)	4	32	0.81	0.81	0.81
68	r5a.2xlarge (Beta)	8	64	1.61	1.61	1.61
69	r5a.4xlarge (Beta)	16	128	3.23	3.23	3.23
70	r5a.8xlarge (Beta)	32	256	3.86	6.46	6.46
71	r5a.12xlarge (Beta)	48	384	3.86	9.69	9.69
72	r5a.16xlarge (Beta)	64	512	3.86	12.91	12.91
73	r5a.24xlarge (Beta)	96	768	3.86	19.37	19.37
74	i3.xlarge	4	30.5	1	1	1
75	i3.2xlarge	8	61	2	2	2
76	i3.4xlarge	16	122	3.86	4	4
77	i3.8xlarge	32	244	3.86	8	8
78	i3.16xlarge	64	488	3.86	16	16
79	i2.xlarge	4	30.5	1.5	1.5	1.5
80	i2.2xlarge	8	61	3	3	3
81	i2.4xlarge	16	122	3.86	6	6
82	i2.8xlarge	32	244	3.86	12	12
83	p2.xlarge	4	61	1.22	1.22	1.22
84	p2.8xlarge	32	488	9.76	9.76	9.76
85	p2.16xlarge	64	732	19.52	19.52	19.52
86	p3.2xlarge	8	61	4.15	4.15	4.15
87	p3.8xlarge	32	244	16.6	16.6	16.6
88	p3.16xlarge	64	488	33.2	33.2	33.2
89	g4dn.xlarge (Beta)	4	16	0.71	0.71	0.71
90	g4dn.2xlarge (Beta)	8	32	1.43	1.43	1.43
91	g4dn.4xlarge (Beta)	16	64	2.85	2.85	2.85
92	g4dn.8xlarge (Beta)	32	128	5.7	5.7	5.7
93	g4dn.12xlarge (Beta)	48	192	8.56	8.56	8.56
94	g4dn.16xlarge (Beta)	64	256	11.41	11.41	11.41
95	z1d.large (Beta)	2	16	0.66	0.66	0.66
96	z1d.xlarge (Beta)	4	32	1.33	1.33	1.33
97	z1d.2xlarge (Beta)	8	64	2.66	2.66	2.66
98	z1d.3xlarge (Beta)	12	96	3.86	3.99	3.99
99	z1d.6xlarge (Beta)	24	192	3.86	7.97	7.97
100	z1d.12xlarge (Beta)	48	384	3.86	15.94	15.94

Select Plan
Standard Premium Enterprise

Compute Type

AWS Instance Type

Hours / Day

Days / Month

Note: This Pricing Calculator provides only an estimate of your Databricks cost. Your actual cost depends on your actual usage. Also, the estimated cost doesn't include cost for any required AWS services (e.g. EC2 instances).

Supported Instance Types

Select Plan

Databricks Compute Type

m4.large	2	8	0.40	0.40	0.40
m4.xlarge	4	16	0.75	0.75	0.75
m4.2xlarge	8	32	1.50	1.50	1.50
m4.4xlarge	16	64	3.00	3.00	3.00
m4.10xlarge	40	160	3.86	8.00	8.00
m4.16xlarge	64	256	3.86	12.00	12.00
m5.large	2	8	0.35	0.35	0.35
m5.xlarge	4	16	0.69	0.69	0.69
m5.2xlarge	8	32	1.37	1.37	1.37
m5.4xlarge	16	64	2.74	2.74	2.74
m5.12xlarge	48	192	3.86	8.23	8.23
m5.24xlarge	96	384	3.86	16.46	16.46
m5d.large (Beta)	2	8	0.34	0.34	0.34
m5d.xlarge (Beta)	4	16	0.69	0.69	0.69
m5d.2xlarge (Beta)	8	32	1.37	1.37	1.37
m5d.4xlarge (Beta)	16	64	2.74	2.74	2.74
m5d.12xlarge (Beta)	48	192	3.86	8.23	8.23
m5d.24xlarge (Beta)	96	384	3.86	16.46	16.46
m5a.large (Beta)	2	8	0.31	0.31	0.31
m5a.xlarge (Beta)	4	16	0.61	0.61	0.61
m5a.2xlarge (Beta)	8	32	1.23	1.23	1.23
m5a.4xlarge (Beta)	16	64	2.46	2.46	2.46
m5a.8xlarge (Beta)	32	128	3.86	4.91	4.91
m5a.12xlarge (Beta)	48	192	3.86	7.37	7.37
m5a.16xlarge (Beta)	64	256	3.86	9.83	9.83
m5a.24xlarge (Beta)	96	384	3.86	14.74	14.74
c3.2xlarge (Deprecated)	8	15	1.00	1.00	1.00
c3.4xlarge (Deprecated)	16	30	2.00	2.00	2.00
c3.8xlarge (Deprecated)	36	60	3.86	4.00	4.00
c4.2xlarge	8	15	1.00	1.00	1.00
c4.4xlarge	16	30	2.00	2.00	2.00
c4.8xlarge	36	60	3.86	4.00	4.00
c5.xlarge	4	8	0.61	0.61	0.61
c5.2xlarge	8	16	1.21	1.21	1.21
c5.4xlarge	16	32	2.43	2.43	2.43
c5.9xlarge	36	72	3.86	5.46	5.46
c5.18xlarge	72	144	3.86	10.92	10.92
c5d.xlarge	4	8	0.69	0.69	0.69
c5d.2xlarge	8	16	1.37	1.37	1.37
c5d.4xlarge	16	32	2.74	2.74	2.74
c5d.9xlarge	36	72	3.86	5.48	5.48
c5d.18xlarge	72	144	3.86	10.96	10.96
r3.xlarge	4	31	1.00	1.00	1.00
r3.2xlarge	8	61	2.00	2.00	2.00
r3.4xlarge	16	122	3.86	4.00	4.00
r3.8xlarge	32	244	3.86	8.00	8.00
r4.xlarge	4	31	1.00	1.00	1.00
r4.2xlarge	8	61	2.00	2.00	2.00
r4.4xlarge	16	122	3.86	4.00	4.00
r4.8xlarge	32	244	3.86	8.00	8.00
r4.16xlarge	64	488	3.86	16.00	16.00
r5.large	2	16	0.45	0.45	0.45
r5.xlarge (Beta)	4	32	0.90	0.90	0.90
r5.2xlarge (Beta)	8	64	1.80	1.80	1.80
r5.4xlarge (Beta)	16	128	3.60	3.60	3.60
r5.8xlarge (Beta)	32	256	3.86	7.20	7.20
r5.12xlarge (Beta)	48	384	3.86	10.80	10.80
r5.16xlarge (Beta)	64	512	3.86	14.40	14.40
r5.24xlarge (Beta)	96	768	3.86	21.60	21.60
r5d.large (Beta)	2	16	0.45	0.45	0.45
r5d.xlarge (Beta)	4	32	0.90	0.90	0.90
r5d.2xlarge (Beta)	8	64	1.80	1.80	1.80
r5d.4xlarge (Beta)	16	128	3.60	3.60	3.60
r5d.12xlarge (Beta)	48	384	3.86	10.80	10.80
r5d.24xlarge (Beta)	96	768	3.86	21.60	21.60
r5a.large (Beta)	2	16	0.41	0.41	0.41
r5a.xlarge (Beta)	4	32	0.81	0.81	0.81
r5a.2xlarge (Beta)	8	64	1.61	1.61	1.61
r5a.4xlarge (Beta)	16	128	3.23	3.23	3.23
r5a.8xlarge (Beta)	32	256	3.86	6.46	6.46
r5a.12xlarge (Beta)	48	384	3.86	9.69	9.69
r5a.16xlarge (Beta)	64	512	3.86	12.91	12.91
r5a.24xlarge (Beta)	96	768	3.86	19.37	19.37
i3.xlarge	4	31	1.00	1.00	1.00
i3.2xlarge	8	61	2.00	2.00	2.00
i3.4xlarge	16	122	3.86	4.00	4.00
i3.8xlarge	32	244	3.86	8.00	8.00
i3.16xlarge	64	488	3.86	16.00	16.00
i2.xlarge	4	31	1.50	1.50	1.50
i2.2xlarge	8	61	3.00	3.00	3.00
i2.4xlarge	16	122	3.86	6.00	6.00
i2.8xlarge	32	244	3.86	12.00	12.00
p2.xlarge GPU This instance also includes the following GPU configuration: 2,496 cores and 12GB of GPU Memory	4	61	1.22	1.22	1.22
p2.8xlarge GPU This instance also includes the following GPU configuration: 19,968 cores and 96GB of GPU Memory	32	488	9.76	9.76	9.76
p2.16xlarge GPU This instance also includes the following GPU configuration: 39,936 cores and 192GB of GPU Memory	64	732	19.52	19.52	19.52
p3.2xlarge GPU This instance also includes the following GPU configuration: 5,120 CUDA cores + 640 Tensor cores and 16GB of GPU Memory	8	61	4.15	4.15	4.15
p3.8xlarge GPU This instance also includes the following GPU configuration: 20,480 CUDA cores + 2,560 Tensor cores and 64GB of GPU Memory	32	244	16.60	16.60	16.60
p3.16xlarge GPU This instance also includes the following GPU configuration: 40,960 CUDA cores + 5,120 Tensor cores and 128GB of GPU Memory	64	488	33.20	33.20	33.20
g4dn.xlarge (Beta) GPU This instance also includes the following GPU configuration: 1 NVIDIA T4 Tensor Core and 16GB of GPU Memory	4	16	0.71	0.71	0.71
g4dn.2xlarge (Beta) GPU This instance also includes the following GPU configuration: 1 NVIDIA T4 Tensor Core and 16GB of GPU Memory	8	32	1.43	1.43	1.43
g4dn.4xlarge (Beta) GPU This instance also includes the following GPU configuration: 1 NVIDIA T4 Tensor Core and 16GB of GPU Memory	16	64	2.85	2.85	2.85
g4dn.8xlarge (Beta) GPU This instance also includes the following GPU configuration: 1 NVIDIA T4 Tensor Core and 16GB of GPU Memory	32	128	5.70	5.70	5.70
g4dn.12xlarge (Beta) GPU This instance also includes the following GPU configuration: 4 NVIDIA T4 Tensor Core and 64GB of GPU Memory	48	192	8.56	8.56	8.56
g4dn.16xlarge (Beta) GPU This instance also includes the following GPU configuration: 1 NVIDIA T4 Tensor Core and 16GB of GPU Memory	64	256	11.41	11.41	11.41
z1d.large (Beta)	2	16	0.66	0.66	0.66
z1d.xlarge (Beta)	4	32	1.33	1.33	1.33
z1d.2xlarge (Beta)	8	64	2.66	2.66	2.66
z1d.3xlarge (Beta)	12	96	3.86	3.99	3.99
z1d.6xlarge (Beta)	24	192	3.86	7.97	7.97
z1d.12xlarge (Beta)	48	384	3.86	15.94	15.94

AWS Pricing FAQs

What is a DBU?

A Databricks Unit (“DBU”) is a unit of processing capability per hour, billed on per-second usage. Databricks supports many AWS EC2 instance types. The larger the instance is, the more DBUs you will be consuming on an hourly basis. For example, 1 DBU is the equivalent of Databricks running on a c4.2xlarge machine for an hour.

What is the difference between Jobs workloads and All-Purpose workloads?

Jobs workloads are workloads running on Jobs clusters. Jobs clusters are clusters that are both started and terminated by the same Job. Only one job can be run on a Jobs cluster for isolation purposes.

All-Purpose workloads are workloads running on All-Purpose clusters. All-Purpose clusters are clusters that are not classified as Jobs clusters. They can be used for various purposes such as running commands within Databricks notebooks, connecting via JDBC/ODBC for BI workloads, running MLflow experiments on Databricks. Multiple users can share a All-Purpose cluster for doing interactive analysis in a collaborative way.

There are two cluster options for jobs – Jobs cluster and Jobs Light cluster. How do I decide which one to use?

Jobs Light cluster is Databricks’ equivalent of open source Apache Spark. It targets simple, non-critical workloads that don’t need the performance, reliability, or autoscaling benefits provided by Databricks’ proprietary technologies. In comparison, the Jobs cluster provides you with all of the aforementioned benefits to boost your team productivity and reduce your total cost of ownership.

What does the free trial include?

The 14-day free trial gives you access to either Standard or Premium feature sets depending on your choice of the plan. Contact us if you are interested in Databricks Enterprise or Dedicated plan for custom deployment and other enterprise customizations.

Note that during trial, AWS will bill you directly for the EC2 instances created in Databricks.

What happens after the free trial?

At the end of the trial, you are automatically subscribed to the plan that you have been on during the free trial. You can cancel your subscription at any time.

What is Databricks Community Edition?

Databricks Community Edition is a free, limited functionality platform designed for anyone who wants to learn Spark. Sign up here.

How will I be billed?

By default, you will be billed monthly based on per-second usage on your credit card. Contact us for more billing options, such as billing by invoice or an annual plan.

Do you provide technical support?

We offer technical support with annual commitments. Contact us to learn more or get started.

I want to process protected health information (PHI) within Databricks / I want a HIPAA-compliant deployment. Is there anything I need to know to get started?

You must contact us for a HIPAA-compliant deployment. Please note that prior to processing any PHI data in Databricks, a signed business associate agreement (BAA) must be in place between your organization and (a) Databricks, Inc.; and (b) because you must have your own account with AWS to deploy Databricks on AWS, Amazon Web Services. Please see here for more details.

For features marked as “(Preview)”, what does that mean? Will these features be automatically turned on?

Please contact us to get access to preview features.

For intra-node encryption for Spark, is there anything I need to do to turn it on?

Yes. We provide our customers with the ability to decide for themselves whether the tradeoffs for additional encryption are necessary given the workloads being processed. Please contact us to enable it.