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It's a split decision.
MongoDB Atlas is a hosted, multi-cloud data platform built around a document model, with search, vector search, transactions and analytics. ScyllaDB is a distributed NoSQL database aimed at high-throughput, low-latency workloads, including feature stores and vector search. Choose Atlas when its broader set of data services and free M0 tier fit your application. Choose ScyllaDB when predictable latency and distributed scale are priorities, and its resource-based pricing or self-managed Enterprise option suits your operations team.
01Side by side
| MongoDB Atlas | ScyllaDB | |
|---|---|---|
| Pricing model | Hourly dedicated tiers; Flex and small tiers monthly | Resource-based Cloud pricing; no per-request charges |
| Free tier | M0 free forever; 512 MB storage | No free plan; 30-day Developer trial |
| Data model | Document model with a query API | Distributed NoSQL database |
| Self-hosting | Yes; Enterprise Advanced for your infrastructure | ScyllaDB Enterprise offers self-managed deployment |
| Deployment model | Atlas across cloud providers or your infrastructure | ScyllaDB Cloud or self-managed Enterprise |
| Integrations | 100+ technologies; Kafka named for stream processing | Homepage names no specific integrations |
| Workload fit | Transactions, search, analytics, vectors and streams | Low-latency AI, feature stores and vector search |
| Scaling claims | Atlas Infinite: up to 128 TB per HA shard | Petabyte storage and billions of embeddings |
MongoDB Atlas Choose MongoDB Atlas if
- Choose MongoDB Atlas if you need document queries, transactions and search in one platform.
- Choose MongoDB Atlas if a free M0 tier helps with learning or exploration.
- Choose MongoDB Atlas if you need named integrations such as Apache Kafka.
ScyllaDB Choose ScyllaDB if
- Choose ScyllaDB if predictable, single-digit millisecond latency is a priority.
- Choose ScyllaDB if your workload needs distributed, high-throughput feature or vector search.
- Choose ScyllaDB if resource-based pricing without per-request charges fits your cost model.
02Pricing at real usage
Atlas has an M0 free tier with 512 MB storage and up to 100 operations per second. Flex is listed at $8–$30 monthly, with 5 GB storage and 0–500 operations-per-second tiers. M2 and M5 cost $9 and $25 per month. Dedicated clusters are billed hourly: M10 starts at $0.08 per hour, M20 at $0.20, and M30 at $0.54. Costs rise with cluster size; Atlas also lists separate charges for some services, such as Data Federation at $5 per TB processed.
ScyllaDB Cloud uses resource-based pricing with no per-request charges, but the vendor doesn't publish monthly or annual plan prices. A 30-day Developer Free Trial and 48-hour Production Evaluation are listed. On-demand hourly rates, Flex Credits, data transfer and backup storage beyond one daily backup can add costs. Ask ScyllaDB for a quote based on region, capacity and contract term.
03API, SDKs and integration
Atlas uses a document model and query API for lookups, processing pipelines, analytics and transformations. Its platform also combines transactions, search, vector search, stream processing and analytics. The MongoDB homepage links to documentation and says Atlas integrates with more than 100 technologies, naming Apache Kafka for stream processing. It does not identify particular SDK languages or a CLI on the homepage.
ScyllaDB is presented as a distributed NoSQL database and a managed Cloud service, with DynamoDB and Cassandra replacements among its use cases. Its homepage does not name specific integrations, SDK languages or a CLI. The sources also do not give protocol-level connection details for either product. Before choosing a driver or planning a migration, check the vendors' current documentation for supported languages, APIs, compatibility requirements and operational tooling. Atlas has a documented entry point linked from its homepage; for ScyllaDB, confirm the relevant driver and integration support for your stack.
04Open source, self-hosting and lock-in
MongoDB Atlas is a hosted platform, and MongoDB also offers deployment on your own infrastructure. Enterprise Advanced is the self-managed option listed for enterprise teams; it has custom pricing and includes a commercial license. ScyllaDB lists Enterprise as a self-managed product, with custom quotes and licensing based on provisioned vCPUs and cluster sizing. Neither product page identifies an open-source license, so check the applicable license terms before building around a self-hosted edition.
The vendors don't publish data-export or migration details on the pages described here. Ask about export formats, ongoing replication, downtime and compatibility before committing. Atlas uses a document model, while ScyllaDB is a distributed NoSQL database; changing between them may require changes to data modeling and application queries. MongoDB lists a Relational Migrator for migration to MongoDB, but that does not establish a reverse migration path.
Questions people ask
Is ScyllaDB open source?
ScyllaDB's homepage does not identify an open-source license. Its pricing information lists ScyllaDB Enterprise as a separately licensed, self-managed option, with custom pricing based on provisioned vCPUs and cluster sizing. Confirm the license terms for the edition you plan to deploy with ScyllaDB.
Are MongoDB and MongoDB Atlas the same?
No. MongoDB Atlas is MongoDB's hosted data platform, while MongoDB also offers self-managed Enterprise Advanced and Community Edition for local development. Atlas adds managed services including database, search and vector search. Choose based on whether you want a hosted service or to manage infrastructure yourself.
Who is MongoDB's biggest competitor?
There isn't enough published information to identify one biggest competitor across MongoDB's workloads. ScyllaDB is an alternative for distributed NoSQL use cases and positions itself as a DynamoDB and Cassandra replacement. Atlas also covers search, analytics and vector workloads, so compare tools against your specific workload.
Is DocumentDB actually MongoDB?
The product details here don't establish whether DocumentDB is MongoDB or define its compatibility. Don't infer equivalence from a shared database category or a product name. Check the vendors' compatibility documentation for supported APIs, query behavior, drivers and migration requirements before treating one as a drop-in replacement for the other.