Sold by: ScyllaDB, Inc
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ScyllaDB Enterprise NoSQL database
4.5
Overview
ScyllaDB Enterprise is the high-performance NoSQL database for real-time big data workloads. It is a wide-column store with APIs compatible with Apache Cassandra CQL and Amazon DynamoDB. ScyllaDB Enterprise is self-tuning upon installation and self-optimizing in production, which means users get optimal performance without spending time constantly tweaking the system. It just runs consistently fast, with consistent low latency. ScyllaDB is designed to take full advantage of NUMA multiprocessor architectures and fast storage, such as those found in AWS I3, i3en, and i4i series instances.
Highlights
- Build highly scalable, highly performant NoSQL-based applications that can support high-throughput (millions of transactions per second per database node) and maintain consistent low single-digit millisecond latencies.
- APIs compatible with Apache Cassandra CQL and Amazon DynamoDB.
- With ScyllaDB hardware efficiency and predictable pricing, users reduce their TCO up to 70% without compromising performance.
Details
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64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
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Try this product free for 7 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
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. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
i3.4xlarge Recommended | $1.63 |
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
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Additional details
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Resources
Vendor resources
Support
Vendor support
Scylladb Enterprise support ensures that users have access to the engineers who develop Scylla via the channels they prefer - the web support, email, Slack, etc. https://www.scylladb.com/scylladb-support-policy/
For additional information, custom pricing, or a private contract, please contact info@scylladb.com .
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 ScyllaDB, Inc
By MongoDB, Inc
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In Databases, Databases & Analytics Platforms
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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
Wide-Column Store Architecture
NoSQL database with wide-column store design supporting high-throughput workloads and real-time big data processing
API Compatibility
Compatible with Apache Cassandra CQL and Amazon DynamoDB APIs
Self-Tuning and Self-Optimizing
Automatic performance tuning upon installation and continuous optimization in production without manual system configuration
NUMA Architecture Optimization
Designed to leverage NUMA multiprocessor architectures and fast storage devices including AWS I3, i3en, and i4i series instances
Low-Latency Performance
Delivers consistent single-digit millisecond latencies with support for millions of transactions per second per database node
Native Vector Search Integration
MongoDB Atlas integrates native vector search directly into the operational database, enabling RAG and agentic AI solutions without requiring separate search infrastructure.
Flexible Document Model
Supports storage and synchronization of structured, unstructured, and semi-structured data types with dynamic schema capabilities for AI-driven applications.
Multi-Workload Unification
Consolidates operational, analytical, and AI workloads within a single database platform.
Industry Compliance Standards
Complies with HIPAA, GDPR, ISO 27001, and PCI DSS standards with built-in security features and encryption.
Elastic Scalability
Supports both vertical and horizontal scaling with configurable cluster configurations to accommodate varying application demands.
Peer-to-Peer Architecture
Utilizes a peer-to-peer architecture enabling horizontal scalability without any single point of failure across distributed systems.
Tunable Consistency Levels
Supports customizable consistency levels allowing developers to balance performance and data consistency based on specific workload requirements.
Schema-Free Data Model
Handles structured, semi-structured, and unstructured data with a schema-free design that adapts to diverse application needs.
Multi-Node Data Distribution
Supports data distribution across multiple nodes providing resilience against hardware failures and continuous operation without downtime.
Pre-Configured Deployment
Comes pre-configured with best practices on Ubuntu 22.04 LTS enabling rapid deployment and seamless integration with AWS services.
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
No security profile
-
No security profile
Standard contract
No
Customer reviews
Vaibhav Y.
Best Performance and Low Latency with NoSQL Database (ScyllaDB)
Reviewed on Feb 24, 2026
Review provided by G2
What do you like best about the product?
I like ScyllaDB's performance, especially because it's impacted by its indexing and the whole database being written in C++, which serves as the building block for a faster NoSQL DB. It's great for storing our ERP system, especially as we introduce new features and are unsure about the schema size. This NoSQL wide column structure allows us to store a wide range of data. Performance is great compared to MongoDB, and it has very low latency. We experienced a decrease in latency while debugging through the log.
What do you dislike about the product?
I find ScyllaDB's UI to be very minimal. It doesn't have native integration for cloud functions like MongoDB or Firebase. Also, live streaming requires extra setup compared to Firebase.
What problems is the product solving and how is that benefiting you?
With ScyllaDB, I don’t need to worry about data size or schema types. It handles our ERP system(Gateway group of companies erp systen) flawlessly with great performance and low latency, improving user experience significantly.
Computer Software
Strong Performance for ML Pipeline with ScyllaDB
Reviewed on Feb 17, 2026
Review provided by G2
What do you like best about the product?
ScyllaDB gives very high performance for our ML pipeline. It uses shard-per-core design, so each CPU core handles its own data. Because of this, read and write speed is very high. It supports high throughput and keeps latency very low even when we store and fetch large training data.
What do you dislike about the product?
Data modeling needs to be done carefully. We must design partition keys properly to get best speed. Monitoring and tuning need some effort when data grows very large.
What problems is the product solving and how is that benefiting you?
We store large ML training and inference data in ScyllaDB. During model training, data is read very fast without delay. High throughput helps us process many records at the same time. Because of this, our ML pipeline runs faster and we complete training jobs in less time.
Verified User in Computer & Network Security
ScyllaDB performs well in every measurable way, throughput, latency, cost, and efficiency.
Reviewed on Feb 05, 2026
Review provided by G2
What do you like best about the product?
Scylladb change in their license policy, which will have an effect for anyone who is self-hosting and using the non-enterprise version.
What do you dislike about the product?
poor documentation with limited features
What problems is the product solving and how is that benefiting you?
ScyllaDB performs well than Cassandra in nearly every measurable way, throughput, latency, cost, and efficiency.
It also simplifies the operations while offering enterprise-grade NoSQL features.Migration is non-disruptive and well-documented, supported by mature tools.
It also simplifies the operations while offering enterprise-grade NoSQL features.Migration is non-disruptive and well-documented, supported by mature tools.
Kaushik V.
Low Latency That Delivers at Scale
Reviewed on Feb 04, 2026
Review provided by G2
What do you like best about the product?
What I like best about ScyllaDB is its performance and efficiency at scale.
What do you dislike about the product?
One thing I dislike about ScyllaDB is that its advanced architecture can raise the learning curve, especially for teams new to distributed systems or coming from traditional databases. Understanding concepts like shard-per-core, tuning, and operational best practices takes time.
What problems is the product solving and how is that benefiting you?
scaling high-throughput, low-latency workloads without excessive infrastructure cost or operational complexity
Legal Services
Best NoSQL Database for Storing non-text data (e.g. BSON)
Reviewed on Dec 23, 2025
Review provided by G2
What do you like best about the product?
Below are the things that I like the most about ScyllaDB:
- Stores millions of legal documents(in bson) without problem
- High throughput helps our ML pipelines run faster
- Indexing is very good and helps in quick search
- Low latency while reading and processing documents
- Stores millions of legal documents(in bson) without problem
- High throughput helps our ML pipelines run faster
- Indexing is very good and helps in quick search
- Low latency while reading and processing documents
What do you dislike about the product?
Nothing to dislike about Scylladb but in our use-case Query patterns must be fixed early.
What problems is the product solving and how is that benefiting you?
- Scylladb Helps us manage huge legal document data easily
- It Makes document analysis fast and reliable due to it's low latency
- Supports ML pipelines with maximum throughput
- It Makes document analysis fast and reliable due to it's low latency
- Supports ML pipelines with maximum throughput