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.
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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
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
PhoenixAI Usage (each unit is 1 percent of standard CCU) | $0.0065 |
Vendor refund policy
No refund
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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
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Support
Vendor support
Email: cloud-support@phoenixdata.ai Phone: 3035201880 https://support.phoenixdata.ai
AWS infrastructure support
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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 existing data lakes
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 enabling direct interaction with object store data
Multi-Cloud Analytics Platform
Connected multi-cloud data platform supporting full integration with SQL, Python, R languages 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 for 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 with Premier Cloud Support
Distributed SQL Database Architecture
Fully managed, distributed SQL database with lock-free cloud-native architecture designed for transactional (OLTP) and analytical (OLAP) workloads
High-Throughput Data Ingestion
Parallel, distributed lock-free ingestion capable of processing millions of events per second using Pipelines
Vector Search Capabilities
Indexed vector search with full-text search capabilities for generative AI applications with elastic scale-out architecture
Real-Time Query Processing
Low-latency SQL query execution on billions of rows of data with support for tens or hundreds of thousands of concurrent users
Unified Workload Engine
Single engine supporting transactional (OLTP), analytical (OLAP), and vector (GenAI) workloads without requiring data movement between systems
Standard contract
No
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Customer reviews
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.
Emre K.
Transforming Big Data with StarRocks
Reviewed on Aug 28, 2025
Review provided by G2
What do you like best about the product?
What I like best about CelerData Enterprise is the combination of outstanding query performance and the strong support from the CelerData team. The product meets our technical needs, and the people behind it make the journey much easier.
What do you dislike about the product?
I can't find anything dislike about CelerData.
What problems is the product solving and how is that benefiting you?
CelerData Enterprise helps us handle very high data ingestion while still being able to run complex queries without impacting system performance.