Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
$18
per month per host
OpenText Vertica
Score 10.0 out of 10
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The Vertica Analytics Platform supplies enterprise data warehouses with big data analytics capabilities and modernization. Vertica is owned and supported by OpenText.
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Snowflake
Score 8.7 out of 10
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The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
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Pricing
Datadog
OpenText Vertica
Snowflake
Editions & Modules
Log Management
$1.27
per month (billed annually) per host
Infrastructure
$15.00
per month (billed annually) per host
Standard
$18
per month per host
Enterprise
$27
per month per host
DevSecOps Pro
$27
per month per host
APM
$31.00
per month (billed annually) per host
DevSecOps Enterprise
$41
per month per host
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Datadog
OpenText Vertica
Snowflake
Free Trial
Yes
No
Yes
Free/Freemium Version
Yes
No
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
Optional
No setup fee
No setup fee
Additional Details
Discount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
We have utilized a SIEM in the past, but it was a very manual process to set it up. Content packs make it very easy to set up and get alerting instantly. Datadog takes out a lot of headaches for our security team, since they no longer have to create custom alerts for every …
SAP HANA, Oracle, MySQL, and PostgreSQL are too heavyweight for achieving real-time latency requirements. Google BigQuery is limited to Cloud that makes hard to integrate with a large ingestion pipeline that may have both Cloud-based and on-prem components. Hadoop is much more …
Datadog may be better suited for teams that have a more out-of-the-box infrastructure, on the primary platforms Datadog supports. You may also have better results if you have a bigger team dedicated to devops and/or a bigger budget. We found that trying to adapt it to our use case (small team, .NET on AWS Fargate) wasn't feasible. We continually ran into roadblocks that required us to dig through documentation (and at times, having to figure out some documentation was wrong), go back and forth with support, and in my opinion, waste money on excessive and unintended usages due to opaque pricing models and inaccurate usage reports, as well as broken/non-functional rate sampling controls.
Vertica as a data warehouse to deliver analytics in-house and even to your client base on scale is not rivaled anywhere in the market. Frankly, in my experience it is not even close to equaled. Because it is such a powerful data warehouse, some people attempt to use it as a transactional database. It certainly is not one of those. Individual row inserts are slow and do not perform well. Deletes are a whole other story. RDBMS it is definitely not. OLAP it rocks.
Snowflake is well suited when you have to store your data and you want easy scalability and increase or decrease the storage per your requirement. You can also control the computing cost, and if your computing cost is less than or equal to 10% of your storage cost, then you don't have to pay for computing, which makes it cost-effective as well.
The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.
Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
Snowflake manages concurrency better in our trials than other premium competitors
Snowflake has little to no setup and ramp up time
Snowflake offers online training for various employee types
Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
I would appreciate more supportive examples for how to filter and view metrics in the explorer
I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame
Could use some work on better integrating with cloud providers and open source technologies. For AWS you will find an AMI in the marketplace and recently a connector for loading data from S3 directly was created. With last release, integration with Kafka was added that can help.
Managing large workloads (concurrent queries) is a bit challenging.
Having a way to provide an estimate on the duration for currently executing queries / etc. can be helpful. Vertica provides some counters for the query execution engine that are helpful but some may find confusing.
Unloading data over JDBC is very slow. We've had to come up with alternatives based on vsql, etc. Not a very clean, official on how to unload data.
Do not force customers to renew for same or higher amount to avoid loosing unused credits. Already paid credits should not expire (at least within a reasonable time frame), independent of renewal deal size.
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.
Because the fact that you can query tons of data in a few seconds is incredible, it also gives you a lot of functions to format and transform data right in your query, which is ideal when building data models in BI tools like Power BI, it is available as a connector in the most used BI tools worldwide.
The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.
I haven't had any recent opportunity to reach out to Vertica support. From what I remember, I believe whenever I reached out to them the experience was smooth.
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.
Key features:
Logs, metrics, and APM (Application Performance Monitoring)
Real-time alerting and dashboards
Supports Kubernetes, AWS, GCP, and other integrations
RUM (Real User Monitoring) and Synthetics
✅ Best for backend, server, and distributed systems monitoring.
Vertica performs well when the query has good stats and is tuned well. Options for GUI clients are ugly and outdated. IO optimized: it's a columnar store with no indexing structures to maintain like traditional databases. The indexing is achieved by storing the data sorted on disk, which itself is run transparently as a background process.
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
