Databricks Lakehouse Platform vs. SingleStore

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Databricks Lakehouse Platform
Score 8.3 out of 10
N/A
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…
$0.07
Per DBU
SingleStore
Score 9.8 out of 10
N/A
SingleStore aims to deliver the world’s fastest distributed SQL database for data-intensive applications: SingleStoreDB, which combines transactional + analytical workloads in a single platform.
$0.69
per hour
Pricing
Databricks Lakehouse PlatformSingleStore
Editions & Modules
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
OnDemand
$0.69
per hour
Offerings
Pricing Offerings
Databricks Lakehouse PlatformSingleStore
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Databricks Lakehouse PlatformSingleStore
Top Pros
Top Cons
Best Alternatives
Databricks Lakehouse PlatformSingleStore
Small Businesses

No answers on this topic

Amazon RDS
Amazon RDS
Score 8.7 out of 10
Medium-sized Companies
Snowflake
Snowflake
Score 9.0 out of 10
Snowflake
Snowflake
Score 9.0 out of 10
Enterprises
Snowflake
Snowflake
Score 9.0 out of 10
SAP IQ
SAP IQ
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Databricks Lakehouse PlatformSingleStore
Likelihood to Recommend
8.4
(17 ratings)
9.8
(56 ratings)
Likelihood to Renew
-
(0 ratings)
9.2
(4 ratings)
Usability
9.4
(3 ratings)
9.1
(7 ratings)
Availability
-
(0 ratings)
9.1
(1 ratings)
Performance
-
(0 ratings)
9.8
(30 ratings)
Support Rating
8.6
(2 ratings)
9.1
(7 ratings)
Implementation Rating
-
(0 ratings)
9.1
(1 ratings)
Contract Terms and Pricing Model
8.0
(1 ratings)
-
(0 ratings)
Ease of integration
-
(0 ratings)
9.1
(1 ratings)
Product Scalability
-
(0 ratings)
9.1
(1 ratings)
Professional Services
10.0
(1 ratings)
-
(0 ratings)
Vendor post-sale
-
(0 ratings)
9.1
(1 ratings)
Vendor pre-sale
-
(0 ratings)
9.1
(1 ratings)
User Testimonials
Databricks Lakehouse PlatformSingleStore
Likelihood to Recommend
Databricks
If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
Read full review
SingleStore
SingleStore HTAP engine is well suited for real-time analytics, fast ingestion, scaling OLTP system like MySQL. When you need to run reports or perform aggregates on billions of rows and you get result in seconds, you cannot get this experience with other OLTP engines. I wish DBtLab was a little more developer and supported for SingleStore. This would allow to perform better data transformation. You can use stored procedures, but DBTLabs has become a standard for dimensional modeling in data warehousing projects. This is probably why SingleStore has trouble piercing in the data warehouse world. It is definately capable to compete with Snowflake when it comes to scalability, query performance, data compression, but Snowflake has ravaged the data warehouse market in few years and large corporations have already invested lots of money in migrating into Snowflake. The SingleStore community needs to grow. Everyone who uses SingleStore loves it.
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Pros
Databricks
  • Process raw data in One Lake (S3) env to relational tables and views
  • Share notebooks with our business analysts so that they can use the queries and generate value out of the data
  • Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
  • Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers
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SingleStore
  • Technical support is stellar -- far above and beyond anything I've experienced with any other company.
  • When we compared SingleStore to other databases two years ago, we found SingleStore performance to be far superior.
  • Pipeline data ingestion is exceptionally fast.
  • The ability to combine transactional and analytical workloads without compromising performance is very impressive.
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Cons
Databricks
  • Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
  • Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
  • Visualization in MLFLOW experiment can be enhanced
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SingleStore
  • We wish the product had better support for High Availability of the aggregator. Currently the indexes generated by the two different aggregators are not in the same sequential space and so our apps have more burden to deal with HA.
  • More tools for debugging issues such as high memory usage would be good.
  • The price was the one that kept us away from purchasing for the first few years. Now we are able to afford due to a promotion that gives it at 25% of the list price. Not sure if we'll continue after the promotion offer expires in another 2 years.
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Likelihood to Renew
Databricks
No answers on this topic
SingleStore
We haven't seen a faster relation database. Period. Which is why we are super happy customers and will for sure renew our license.
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Usability
Databricks
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX
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SingleStore
[Until it is] supported on AWS ECS containers, I will reserve a higher rating for SingleStore. Right now it works well on EC2 and serves our current purpose, [but] would look forward to seeing SingleStore respond to our urge of feature in a shorter time period with high quality and security.
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Reliability and Availability
Databricks
No answers on this topic
SingleStore
We have not experienced any downtime in the two years that we have been using SingleStore.
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Performance
Databricks
No answers on this topic
SingleStore
SingleStore's performance is incredible. Our predictive algorithms went from taking 24-48 HOURS down to 15 minutes allowing our team to run those much more frequently. Previously, we were limited to about 60 requests per minute due to table locks. Implementing columnstore on SingleStore allowed us to receive 1000 requests per minute.
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Support Rating
Databricks
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
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SingleStore
Very responsive to trouble tickets - Often, I think, the SingleStore's monitoring systems have already alerted the engineers by the time I get around to writing a ticket (about 10 - 20 mins after we see a problem). I feel like things are escalated nicely and SingleStore takes resolving trouble tickets seriously. Also SingleStore follows up after incidents to with a post mortem and actionable takaways to improve the product. Very satisfied here.
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Implementation Rating
Databricks
No answers on this topic
SingleStore
We allowed 2-3 months for a thorough evaluation. We saw pretty quickly that we were likely to pick SingleStore, so we ported some of our stored procedures to SingleStore in order to take a deeper look. Two SingleStore people worked closely with us to ensure that we did not have any blocking problems. It all went remarkably smoothly.
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Alternatives Considered
Databricks
Compared to Synapse & Snowflake, Databricks provides a much better development experience, and deeper configuration capabilities. It works out-of-the-box but still allows you intricate customisation of the environment. I find Databricks very flexible and resilient at the same time while Synapse and Snowflake feel more limited in terms of configuration and connectivity to external tools.
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SingleStore
Timescale was the biggest alternative option we looked at for SingleStore, however the requirement to learn a new syntax (due to not being SQL compatible) was our biggest pain point. Supporting a new language would require alterations to the Laravel framework, as this only offered SQL integration out of the box. This alteration would be time consuming and would limit our scope to future hiring due to the new syntax.
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Scalability
Databricks
No answers on this topic
SingleStore
We needed more memory on our cluster. SingleStore handled it very smoothly.
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Return on Investment
Databricks
  • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
  • DB has the ability to terminate/time out instances which helps manage cost.
  • The ability to quickly access typical hard to build data scenarios easily is a strength.
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SingleStore
  • As the overall performance and functionality were expanded, we are able to deliver our data much faster than before, which increases the demand for data.
  • Metadata is available in the platform by default, like metadata on the pipelines. Also, the information schema has lots of metadata, making it easy to load our assets to the data catalog.
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ScreenShots