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Join our hands-on workshop where you’ll learn how to deliver sub-second analytics over TB-scale datasets

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RSVP
Snowflake Amazon Redshift Firebolt
title spanning full row
Elasticity - separation of storage and compute Yes Redshift RA3, Spectrum only Yes
Supported cloud infrastructure AWS, Azure, Google Cloud AWS only AWS only
Tenancy - option for dedicated resources Multi-tenant dedicated resources (Only VPS isolated) Isolated tenant, use own VPC Isolated tenancy Compute and storage
Compute - instance types 1-128 nodes, unknown types Any size, and types 1-128 choice of any types
Data - internal/external, writable storage External tables supported Internal writable, external (Spectrum) External tables (used for ingestion), supports updates
Security - data Separate customer keys (only VPS is isolated tenant,Encryption at rest, RBAC Isolated/VPC tenant for storage and compute, Encryption at rest, RBAC Isolated tenant for storage and compute, Encryption at rest, RBAC
Security - network Firewall, SSL, PrivateLink whitelist/blacklist control, isolated for VPS only Firewall, SSL, PrivateLink whitelist/blacklist control, isolated/VPC tenancy Firewall and WAF, SSL, PrivateLink whitelist/blacklist control, isolated tenancy
Redshift
1st generation

Firebolt
3rd generation
test
Supported cloud infrastructureAWS onlyAWS onlytest
Isolated tenancy – option for dedicated resourcesIsolated tenant, use own VPCMulti-tenant dedicated resourcestest
Compute – node typesAny size, and types1-128 choice of any typestest
Data – internal/external, writable storageInternal writable, external (Spectrum)External tables (used for ingestion)test
Security – dataIsolated/VPC tenant for storage and compute
Encryption at rest, RBAC
Dedicated resources for storage and compute
Encryption at rest, RBAC
test
Security – networkFirewall, SSL, PrivateLink whitelist/ blacklist control, isolated/VPC tenancyFirewall and WAF, SSL, PrivateLink whitelist/ blacklist control
Scalability
Elasticity – (individual) query scalabilityManual1-click cluster resize of node type, number of nodes
Elasticity – user (concurrent query) scalabilityAutoscale up to 10 clusters, 15 queries per cluster, 50 queued queries total, maxUnlimited manual scaling
Write scalability – batch1 master clusterStrong. Multi-master parallel batch
Write scalability – continuousLimited (table-level locking)Multi-master continuous writes
Data scalabilityOnly with RA3: 128 RA3 nodes, 8PB of data.No limit

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Engineering

Python Data Engineer

Product Management

Solution Architect

Design

UX/UI Product designer

HR

Global talent acquisition manager

Marketing

Marketing manager

Operations

Office manager

Sales

Office manager

USA & EMEA
Remote

The fastest way
to build the fastest data experiences

Query #1

Query #2

Query #3

Query #5

Query #4

Queries

Duration

Examined queries durations:

Duration

Performance boost

62 sec

72 sec

90 sec

60 sec

83 sec

0.16 sec

0.09 sec

1.88 sec

0.01 sec

1.6 sec

x388

x800

x48

x6000

x50

Leading data
cloud vendor

$16/hour

Warehouse size:
Large

$1.54/hour

Engine:
1 x c5d.4xlarge

Up to 6000X
performance boost!

Disclaimer - This is not a global benchmark. The results are based on real world queries and run-times as reported by our users over their data cloud vendor, and their equivalent run-times over the same data in Firebolt after tuning and optimization

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Faster than anything you’ve seen, at data-lake scale

Faster than anything you’ve seen, at data-lake scale

Deliver sub-second and highly concurrent analytics experiences over big and granular data, fueled by Firebolt’s storage and compute-optimized technology.

Engineers love Firebolt

Thumbs Up
Quote

Whether we have 100, 200, or 250 users accessing a BI tool, we need consistent sub-second query performance. Firebolt is a key partner for us.

Alan O'Neill
Jeremy Stroud
Director IT Architecture
IQVIA
Thumbs Up
Quote

Firebolt immediately gave us faster performance at a much greater scale, which let our customers analyze huge datasets with sub-second performance. It also gave us the flexibility to deliver complex data features at a much faster pace.

Yoav Shmaria
Yoav Shmaria
VP R&D, Platform.
SimilarWeb
Thumbs Up
Quote

Firebolt is a massive improvement to our BI efforts. Using the same test dataset of 100 million records, other databases took minutes, Firebolt analyzed in seconds.

Alexandra Sudilovski
Yaron Cohen-Leo
BI Team Lead
Bigabid

See how Firebolt works

Fill in your details and schedule a call
Introductory call to have all your questions answered
See how Firebolt solves your most challenging use-case
We give you the keys, now you can use Firebolt yourself and explore additional use-cases

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People say

Firebolt has outperformed all other data serving SQL engines we have tested. It is built by engineers - for engineers

Roy Miara
Engineering Manager
Explorium

Firebolt immediately gave us faster performance at a much greater scale, which let our customers analyze huge datasets with sub-second performance. It also gave us the flexibility to deliver complex data features at a much faster pace

Yoav Shmaria
VP R&D, Platform.
SimilarWeb

With Firebolt, our 1000 Looker users can now run any analytics against billions of rows and terabytes of data, in seconds or less.

Alexandra Sudilovski
S. BI Expert
AppsFlyer

Join our hands-on workshop where you’ll learn how to deliver sub-second analytics over TB-scale datasets

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