Databricks on AWS

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 (Beta)	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	8	15	1	1	1
28	c3.4xlarge	16	30	2	2	2
29	c3.8xlarge	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 (Beta)	72	144	3.86	10.92	10.92
38	c5d.xlarge (Beta)	4	8	0.69	0.69	0.69
39	c5d.2xlarge (Beta)	8	16	1.37	1.37	1.37
40	c5d.4xlarge (Beta)	16	32	2.74	2.74	2.74
41	c5d.9xlarge (Beta)	36	72	3.86	5.48	5.48
42	c5d.18xlarge (Beta)	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	4	32	0.9	0.9	0.9
54	r5.2xlarge	8	64	1.8	1.8	1.8
55	r5.4xlarge	16	128	3.6	3.6	3.6
56	r5.12xlarge	48	384	3.86	10.8	10.8
57	r5.24xlarge (Beta)	96	768	3.86	21.6	21.6
58	r5d.large (Beta)	2	16	0.45	0.45	0.45
59	r5d.xlarge (Beta)	4	32	0.9	0.9	0.9
60	r5d.2xlarge (Beta)	8	64	1.8	1.8	1.8
61	r5d.4xlarge (Beta)	16	128	3.6	3.6	3.6
62	r5d.12xlarge (Beta)	48	384	3.86	10.8	10.8
63	r5d.24xlarge (Beta)	96	768	3.86	21.6	21.6
64	r5a.xlarge (Beta)	4	32	0.81	0.81	0.81
65	r5a.2xlarge (Beta)	8	64	1.61	1.61	1.61
66	r5a.4xlarge (Beta)	16	128	3.23	3.23	3.23
67	r5a.8xlarge (Beta)	32	256	3.86	6.46	6.46
68	r5a.12xlarge (Beta)	48	384	3.86	9.69	9.69
69	r5a.16xlarge (Beta)	64	512	3.86	12.91	12.91
70	r5a.24xlarge (Beta)	96	768	3.86	19.37	19.37
71	i3.large	2	15.3	0.75	0.75	0.75
72	i3.xlarge	4	30.5	1	1	1
73	i3.2xlarge	8	61	2	2	2
74	i3.4xlarge	16	122	3.86	4	4
75	i3.8xlarge	32	244	3.86	8	8
76	i3.16xlarge (Beta)	64	488	3.86	16	16
77	i2.xlarge	4	30.5	1.5	1.5	1.5
78	i2.2xlarge	8	61	3	3	3
79	i2.4xlarge	16	122	3.86	6	6
80	i2.8xlarge	32	244	3.86	12	12
81	p2.xlarge	4	61	1.22	1.22	1.22
82	p2.8xlarge	32	488	9.76	9.76	9.76
83	p2.16xlarge	64	732	19.52	19.52	19.52
84	p3.2xlarge	8	61	4.15	4.15	4.15
85	p3.8xlarge	32	244	16.6	16.6	16.6
86	p3.16xlarge (Beta)	64	488	33.2	33.2	33.2
87	z1d.large (Beta)	2	16	0.66	0.66	0.66
88	z1d.xlarge (Beta)	4	32	1.33	1.33	1.33
89	z1d.2xlarge (Beta)	8	64	2.66	2.66	2.66
90	z1d.3xlarge (Beta)	12	96	3.86	3.99	3.99
91	z1d.6xlarge (Beta)	24	192	3.86	7.97	7.97
92	z1d.12xlarge (Beta)	48	384	3.86	15.94	15.94

Pricing Estimator

Use this estimator to understand how Databricks charges for different workloads

Operational Security
No Yes

Cluster Type

Hours / Day

Days / Month

Please note that the specific instances chosen and amount of usage are very specific to your workload (ETL, streaming, ad-hoc queries, etc.). Engaging with your Databricks contact will help you select appropriate values. The estimator calculates your Databricks usage charges only (and does not include other fees that may be applicable like platform charges). Please discuss with your Databricks contact regarding single-tenant use.

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. See the full list of supported instances and details.

What is the difference between Automated Clusters and Interactive Clusters?

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

Interactive workloads are workloads running on interactive clusters. Interactive clusters are clusters that are not classified as automated 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 an interactive cluster for doing interactive analysis in a collaborative way.

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

Data Engineering Light 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 Data Engineering cluster provides you with all of the aforementioned benefits to boost your team productivity and reduce your total cost of ownership.

What’s the difference between production and interactive analysis workloads?

Production workloads (automated workloads) are defined as jobs that both start and terminate the clusters on which they run. For example, a workload may be triggered by the Databricks Job Scheduler which launches a new Apache Spark cluster solely for the job and automatically terminates the cluster after the job is complete.

Interactive analysis workloads are workloads that are not automated workloads, e.g., running a command within Databricks notebooks. These commands run on Apache Spark clusters that may persist until manually terminated. Multiple users can share a cluster for doing interactive analysis in a collaborative way.

What does the free trial include?

The 14-day free trial gives you access to all Databricks features except the Databricks Operational Security Package and Custom Deployment options. Contact us if you are interested in Databricks Operational Security and / or Custom Deployment options.

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 Databricks without Databricks Enterprise Security. 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.