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INTRODUCING UPSOLVER SQLAKE
BUILD PIPELINES. NOT DAGS.
* Streaming plus batch in a single pipeline platform
* No Airflow - orchestration inferred from data
* $99 / TB of data ingested | unlimited free pipelines
Try for free Watch Video
No credit card required
Pricing Live CTO Talk Free Workshop Builders Hub
$99 per TB Ingested | Transformations Free | 30 Day Unlimited Trial
Using Upsolver, we were analytics-ready and in production within 30 days with
our existing staff.
Learn how Cox Automative modernizes log analytics at scale
With Upsolver, we had a data lake driving real value to our customers in weeks.
Without it, it would have taken us months.
Learn how Proofpoint builds agile and scalable streaming pipelines
AWS led us to Upsolver. We saved months and didn't expend coding-heavy resources
on data pipelines and infrastructure.
Learn how Sisense drives new insights from Amazon S3
'Don’t reinvent the wheel' is one of the pillars of our data strategy. With
Upsolver, I can see the most up-to-date data on Amazon S3, and I don’t need to
manage complex architecture that provides the same functionality.
Learn how Clearly built a High-performance, Low-maintenance Cloud Data Platform
I told the Upsolver guys that I really don't need them anymore because
everything just works. The adoption was really fast.
Learn how AppsFlyer cut compute costs by 75% (over $1m/year saved).
Upsolver has saved thousands of engineering hours and significantly reduced
total cost of ownership, which enables us to invest these resources in
continuing our hypergrowth rather than data pipelines
Learn how IronSource collects, stores, and prepares +20,000,000,000 events daily
I chose Upsolver because time-to-analytics over Amazon S3 is 20X faster compared
to Spark. Our existing staff deployed a production-ready solution within one
month, which eliminated the risk of not being able to replace IBM Netezza on
schedule.
Learn how Peer39 contextualizes billions of pages for targeting and analytics
Upsolver plays a crucial part in our core data infrastructure, and the team has
proven to be a reliable partner that’s been committed to our success from day
one.
Learn how Bigabid built a state-of-the-art mobile marketing and real-time
bidding using Upsolver
Upsolver is completely self-serve. My team quickly became proficient with the
platform, and our first stream was up in less than a day.
Learn how Clinch doubled the number of features available to clients every month
I used to spend dozens of hours on infrastructure - today I spend virtually
none. Upsolver has made my life way better because now I can actually work on
developing new features rather than coding and maintaining ETL pipelines/mark>.
Learn how a single data engineer manages ETL pipelines for 4bn events
With Spark, it used to be that every dashboard was considered ‘untouchable’ – as
long as it was working, we didn’t want to break anything. Since we’ve started
using Upsolver, we can make any change we want, it happens in literally minutes
and it just works.
Learn how VICOMI cut dev ops time from weeks to minutes by switching from spark
to upsolver
Upsolver makes big data much easier than it would be if we had to research all
of the technology it covers. Furthermore, Upsolver has been very responsive to
our requests for help and enhancements. Their support is phenomenal.
How the Meet Group extracted real-time insights from streaming data using
Upsolver and Amazon Athena
Upsolver provides us peace of mind, because now that we store everything in the
data lake, I can reprocess the data in case we make a mistake or need to add new
fields.”
Learn how Gamoshi Saved 75% on real-time pipelines with Upsolver and AWS
Upsolver's ETL pipeline helped improve our efficiency and reduce the time from
ingestion to insight from 24 hours to minutes.
Learn how SimilarWeb analyzes hundreds of terabytes of data with Amazon Athena
and Upsolver
THE BROKEN PIPELINE DEVELOPMENT PROCESS
When you query a database, it automatically generates an execution plan. While a
data pipeline is just query logic that runs continuously, data engineers are
forced to spend countless hours manually building execution plans – a.k.a.
coding orchestration DAGs.
Having to manually orchestrate data pipelines leads to:
* Long analytics cycles – every pipeline is an engineering project
* Unreliable and untrustworthy data
* High cost from poorly optimized pipelines
* Data engineering burnout from frequent break-fix cycles
* Frustrated data consumers who can’t self-serve raw data
WRITE A QUERY -> GET A PIPELINE
With SQLake, you use SQL to ingest streams and files into data lake tables and
then create jobs which transform, join, and aggregate that data, and stream it
into destination systems for analytics consumption.
HOW SQLAKE SIMPLIFIES PIPELINES FOR DATA-IN-MOTION
UNIFY BATCH & STREAMING
Batch and stream processing has traditionally required separate tools and
skills. We unify batch and streaming sources into a single stream processing
flow that minimizes complexity.
ESCAPE DAG HELL
Mapping all pipeline success and failure modes is manual work in Airflow. It’s
hard, time consuming and error-prone. SQLake’s unique architecture
deterministically guarantees correct results in all cases.
AVOID STICKER SHOCK
Predictable, affordable pricing. You only pay for data you ingest ($99/TB, or <
10 cents / GB), which is retained and managed in the data lake. You build
unlimited transformation pipelines for free.
Try For Free
CHECK OUT OUR SQLAKE HOW-TO GUIDES
KAFKA TO SNOWFLAKE (STREAMING JOIN)
S3 TO ATHENA (MATERIALIZED VIEW)
UPSERTS FROM S3 INTO ATHENA
REAL-TIME INGESTION FROM KAFKA TO ATHENA
How To Guides
POWERING OVER 7,600 PIPELINES FOR DATA-IN-MOTION
CHECK OUT THE PIPELINE BUILDERS HUB
* Pipeline Templates
* Documentation
* How-to Guides
* Technical Blogs
Visit Builders Hub
SMARTER DATA ARCHITECTURE STARTS HERE
RESOURCES FOR DATA MASTERMINDS
FREE GUIDE
Learn what’s the best way to design and build a data platform that’s aligned
with your use cases.
Read guide
FREE EBOOK
Understand data lake architecture best practices in this practical handbook for
data engineers, data scientists and data architects.
Get Access
COMPARISON GUIDE
Learn how Upsolver’s technology differs from platforms built on Apache Spark in
our comprehensive guide.
Download Now
SQLAKE - FREE FOR FIRST 30 DAYS
BUILD PIPELINES. NOT DAGS.
Unlimited 30 day trial
No credit card required
Start for Free
UPSOLVER
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PRODUCT
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RESOURCES
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BLOG
* Why we built a SQL-based solution to unify batch and stream workflows
* How to Build a MySQL CDC Pipeline in Minutes
* How to publish data to another AWS account’s catalog
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