Sold by: PhoenixAI
Deployed on AWS
PhoenixAI Enterprise is a real-time analytical database for AI agents and customer-facing analytics. It serves sub-second SQL across streaming data and your Apache Iceberg lakehouse, with minimal data movement.
4.6
Overview
PhoenixAI Enterprise is a real-time analytical database for AI agents and customer-facing analytics. It serves sub-second SQL across streaming data and your Apache Iceberg lakehouse, with minimal data movement.
It handles workloads that break other databases: agent queries needing sub-second answers, complex multi-table joins on fresh data, and customer-facing analytics at tens of thousands of QPS. Standard SQL throughout, so existing tools connect without rewrites.
PhoenixAI Enterprise is the enterprise level, self-managed offering of the industry leading MPP database, StarRocks, provided by PhoenixAI.
Core Capabilities include
Sub-second SQL on real-time and historical data PhoenixAI keeps query latency under a second across both freshly streamed data and historical lakehouse data, under the high concurrency AI agents and customer-facing analytics demand. Latency stays stable whether traffic is hundreds of QPS or tens of thousands.
Complex multi-table queries without precomputation
AI agents and dashboards issue queries you can not always plan for. PhoenixAI runs multi-table joins on the fly against normalized schemas, with no need to pre-flatten or pre-aggregate. Materialized views stay available as optional accelerators for the heaviest repeat patterns, not as a mandatory starting point.
Fits into your existing data stack
PhoenixAI sits alongside the infrastructure you already have. Query your lakehouse in place, ingest streams as they arrive, and connect through standard SQL, without rewriting queries, replacing tools, or copying data into a separate warehouse.
Governed access with BYOC
Enterprise governance is built into the database, not bolted on. Fine-grained access controls, per-query audit lets your data and security teams keep enforcement and sovereignty in their own hands.
Highlights
- 1. Cost-Based Query Optimizer 2. SIMD-Optimized Vectorized Execution 3. Massively Parallel Processing Architecture 4. Eliminate De-Normalized Tables 5. Ready to Scale When You Are 6. Achieve True Real-Time Analytics
Details
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Features and programs
Trust Center
Access real-time vendor security and compliance information through their Trust Center powered by Drata or Vanta. Review certifications and security standards before purchase.
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
CPU Cores | Number of CPU cores deployed in the cluster | $175.00 |
Dimensions summary
This contract charges by a single dimension: the number of CPU cores deployed in your cluster. You commit under a contract and scale cost by adding or removing cores. Pricing tracks the compute footprint of your deployment rather than query volume, users, or data stored. As your cluster grows, cost grows with the core count. This suits a real-time analytical database sized to your data volume. You deploy inside your own cloud account or self-host on your own infrastructure.
Top-of-mind questions for buyers
Billing tracks the number of CPU cores across the hosts in your deployed cluster. Each node in the cluster contributes its cores to the total count. The cost reflects your compute footprint, not the number of queries, users, or amount of data you store.
No. Cost tracks CPU cores in your cluster, not query volume or concurrent users. You can sustain high query rates without the bill changing, as long as your core count stays the same. Cost only changes when you add or remove cores.
Yes. You can deploy inside your own cloud account under a shared responsibility model, where the vendor manages the platform and you manage infrastructure. You can also self-manage on bare metal, Kubernetes, or private environments. Core count drives cost in both cases.
www.phoenixdata.ai+1
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Vendor refund policy
No refund.
Custom pricing options
Request a private offer to receive a custom quote.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By PhoenixAI
By Teradata
By SingleStore
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10
In Data Warehouses
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In Business Intelligence
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10
In Analytic Platforms, Databases & Analytics Platforms, Databases
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Query Optimization
Cost-based query optimizer that determines optimal execution plans for complex multi-table joins and analytical queries
Vectorized Execution Engine
SIMD-optimized vectorized execution for accelerated query processing across streaming and historical data
Parallel Processing Architecture
Massively parallel processing architecture enabling sub-second SQL query latency at tens of thousands of queries per second
Data Integration
Support for Apache Iceberg lakehouse integration with minimal data movement, enabling queries across streaming data and historical data in place
Access Control and Governance
Fine-grained access controls and per-query audit capabilities for enterprise governance and data sovereignty
Native Object Store Capabilities
Native Object Store (NOS) Read/Write functionality for direct interaction with object store data
Multi-Cloud Analytics Platform
Connected multi-cloud data platform supporting full integration with SQL, Python, R, and data sources including object stores and HDFS
Advanced Analytics Functions
4D analytics, nPath, sessionization, attribution, and scoring capabilities for descriptive, diagnostic, predictive, and prescriptive analytics
Amazon S3 Integration
Direct integration with Amazon S3 enabling backup, restore, and optional direct querying of object store data
Included Management Tools
Rights to use Teradata Data Stream Controller, Ecosystem Manager, Query Service, Server Management, and Viewpoint tools
Distributed SQL Database Architecture
Fully managed, distributed SQL database with lock-free cloud-native architecture designed for transactional (OLTP) and analytical (OLAP) workloads in a single engine
High-Throughput Data Ingestion
Parallel, distributed lock-free ingestion capable of processing millions of events per second with real-time query processing on billions of rows
Vector Search Capabilities
Indexed vector search with full-text search capabilities optimized for generative AI applications and semantic search operations
Concurrent User Scalability
Cloud-native elastic scale-out architecture supporting tens or hundreds of thousands of concurrent users with super-low latency query performance
Unified Workload Processing
Single engine capability to power high-performance transactional, analytical, and vector workloads simultaneously without requiring data movement between systems
Standard contract
No
No
Customer reviews
Jorge Novo
Centralized analytics has improved real-time campaign reporting and accelerated dashboard insights
Reviewed on Sep 03, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for CelerData is data analytics.
I primarily use CelerData for data analytics at CVS Health, examining models for future campaigns and using different data types and subsets to generate reports and dashboards.
In addition to that, I also use CelerData for migration of data from MySQL to StarRocks database and to set up data within Fanatics, moving data from Postgres into StarRocks, as well as for modifications and transformation of JSON payload packages.
What is most valuable?
The best features CelerData offers include loading data, data broker, CP, CTA, and creating catalogs to point to data sets outside of StarRocks.
When I mention data pro TTA and pointing to data sets outside, I find that these features help us by allowing me to point to S3 buckets holding data files, and by using the catalog to create catalogs for those specific points, I am able to query the data in a faster manner instead of using Athena from AWS, S3, or DataBricks.
CelerData has positively impacted my organization by providing faster response times on reports, especially for real-time data, and I am finally able to centralize all integrated data from different systems for dashboards and reporting.
I have seen response times improve drastically, going from seconds to sub-seconds query responses, and I also improved deployment speed by using Iceberg integration into CelerData catalogs, allowing me to have stream data and real-time data analytics.
What needs improvement?
CelerData can be improved in several areas.
I have identified issues where the transportation and documentation do not reflect the reality of the models, and I found data points issues related to bugs in the code, so for the open-source version, CelerData needs to be more consistent and reliable compared to the cloud version.
Regarding CelerData's AI capabilities, I believe the governance and security need to be tested and integrated, and it is still too early in development to make a good determination.
Concerning CelerData's AI capabilities, the accuracy and reliability of output depend significantly on the quality of log troubleshooting, which I believe is one of the most important parts.
For how long have I used the solution?
I have been using CelerData for seven years.
What do I think about the stability of the solution?
In my experience, CelerData is stable now.
What do I think about the scalability of the solution?
CelerData's scalability has been really reliable for me, accommodating the number of FTE.
How are customer service and support?
The customer support for CelerData has been really good, providing a swift response to my needs.
Which solution did I use previously and why did I switch?
Before CelerData, I initially used Postgres for analytics on Fanatics.
What was our ROI?
I have seen a return on investment with CelerData, as I am now able to have faster responses within my reports.
What's my experience with pricing, setup cost, and licensing?
I have no comments regarding pricing, setup cost, and licensing.
Which other solutions did I evaluate?
Before choosing CelerData, I evaluated other options, including Trino and AWS services.
What other advice do I have?
To others looking into using CelerData, my advice is to get familiar with how a column-based database system works and not to treat it as a relational database. I would rate this product eight out of ten.
reviewer2784384
Building a customer lakehouse has accelerated creation of new BI analytics
Reviewed on Jan 14, 2026
Review from a verified AWS customer
What is our primary use case?
My main use case for CelerData is to use it as a lakehouse and for BI analytics. I use CelerData to build a customer data lakehouse and use that in order to execute SQL queries and build some analytics.
What is most valuable?
The best features CelerData offers are the easy-to-use tools in order to build new analytics. The tools are easy to use for me because of the interface.
CelerData has positively impacted my organization because we improved the production of new analytics. We improved the production by 30%.
What needs improvement?
If I had to think of one area where CelerData could be improved, it would be the documentation.
For how long have I used the solution?
I have been using CelerData for one year.
What do I think about the stability of the solution?
CelerData is stable.
What do I think about the scalability of the solution?
CelerData's scalability is good.
How are customer service and support?
I never interacted with CelerData's support team.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
I did not use a different solution before CelerData.
How was the initial setup?
I had a good experience with pricing, setup cost, and licensing.
What was our ROI?
It is not possible for us to share information about a return on investment.
What's my experience with pricing, setup cost, and licensing?
I had a good experience with pricing, setup cost, and licensing.
Which other solutions did I evaluate?
I did not evaluate other options before choosing CelerData.
What other advice do I have?
My advice for others looking into using CelerData is to try fast and fail fast. I am providing this review with a rating of 10.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
reviewer2784744
Agile data ingestion has accelerated our finance workflows and reduces time to market
Reviewed on Dec 04, 2025
Review provided by PeerSpot
What is our primary use case?
My main use case for CelerData is in a finance customer use case. I use CelerData to ingest data, and ingesting data is the primary way I use CelerData.
What is most valuable?
I appreciate CelerData for the agility we have to ingest data. CelerData's agility is beneficial for us in our workflows. CelerData has positively impacted my organization as it reduced the time to market.
What needs improvement?
CelerData could be improved in the user experience. I do not have specific pain points regarding the needed improvements in the user experience.
For how long have I used the solution?
I have been using CelerData for one year.
What do I think about the stability of the solution?
CelerData is stable.
What do I think about the scalability of the solution?
CelerData's scalability is good.
How are customer service and support?
The customer support for CelerData is good.
Which solution did I use previously and why did I switch?
I did not previously use a different solution.
What was our ROI?
I have no metrics related to return on investment.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing is good.
Which other solutions did I evaluate?
No options were evaluated before choosing CelerData.
What other advice do I have?
I would rate CelerData an eight on a scale of one to ten. I choose eight because I enjoy working with CelerData. I do not have advice for others looking into using CelerData.
Zhenxiao L.
Impressive Query Speed, No Complaints
Reviewed on Oct 30, 2025
Review provided by G2
What do you like best about the product?
fast query speed, good support, running reliable
What do you dislike about the product?
everything is good, nothing bad, customer is happy
What problems is the product solving and how is that benefiting you?
provide fast query speed for real time use cases, e.g. advertisement, trust and safety
Ye Z.
A powerful SQL engine for your most demanding workloads
Reviewed on Sep 03, 2025
Review provided by G2
What do you like best about the product?
What I appreciate most about Celerdata is its incredibly fast query performance, powered by StarRocks, and its world-class support team. This combination allows customers to confidently and easily transform their data strategy at scale.
What do you dislike about the product?
I haven't personally encountered any obvious downsides with Celerdata. The solution is already trusted by a lot of well-known customers, and the support team is incredible. They always go out of their way to help, so if any issues ever pop up, I know they'll be handled right away.
What problems is the product solving and how is that benefiting you?
Celerdata Cloud, powered by StarRocks, addresses a critical problem for businesses: the need for extremely fast and reliable data analysis on massive datasets. Although other solutions exist in this space, StarRocks stands apart. Its superior query performance, especially when handling massive, complex datasets and queries, is a game-changer. This capability is essential for any application requiring real-time insights and for running ad-hoc queries without frustrating wait times.