# supermemory vs TiDB Cloud

supermemory records 156,579 monthly visits with -7.7% month-over-month growth and Contact for Pricing pricing. TiDB Cloud records 61,010 monthly visits with -17.9% growth and Contact for Pricing pricing.

| Metric | [supermemory](https://openaitools.app/tool/supermemory-1) | [TiDB Cloud](https://openaitools.app/tool/tidb) |
| :--- | :--- | :--- |
| Website URL | https://supermemory.ai | https://tidbcloud.com |
| Categories | AI API, Large Language Models (LLMs), AI Developer Tools, AI Agent | Other |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 156,579 | 61,010 |
| MoM Growth Rate | -7.7% | -17.9% |
| Primary Market | United States | India |
| Direct Visits | 71,163 | 40,552 |
| Review Score | 4.5 | 4.6 |
| Saved Count | 0 | 1 |
| Supported Platforms | Website | Website |

## supermemory

Most LLM applications treat memory as an afterthought: chat history is stuffed into the prompt until the window fills up, and everything is lost on the next session or the next model switch. supermemory attacks that problem as infrastructure. Its learner-1 model reads incoming material — conversations, files, URLs, raw data — and performs update, merge, infer and forget operations against a vector-graph database, so learnings stay dense, interconnected and time-aware rather than piling up as an ever-growing transcript.

At request time the relevant memories are injected as tokens directly into the agent's context, which keeps the approach model-agnostic and harness-agnostic. Because learning and memory live outside the model providers, the same accumulated understanding travels with an application whether it runs on Claude, GPT-family models, Gemini or open-weight models, and whether it is driven by an SDK, a plugin or MCP.

The company positions this as the hard part of agent infrastructure and backs it with published numbers: sub-second recall on production traffic, roughly a trillion tokens processed per month, benchmarks on LongMemEval, LoCoMo and ConvoMem, and cost comparisons against markdown-file memory at large corpora. Enterprise features include SOC 2 Type II certification, a HIPAA BAA on higher tiers, GDPR compliance and deployment options ranging from cloud to VPC, on-premises and air-gapped environments.

**Pricing & Plans:** Pricing is split between self-serve tiers and enterprise contracts, which is why the site lists a contact-for-pricing model. Free, Pro and Max tiers cover standard PDF extraction and personal use, while Scale and Enterprise add advanced document extraction with OCR and figure/diagram descriptions, higher limits, security guarantees such as SOC 2 Type II and HIPAA BAA, and deployment choices including your VPC, your data center or air-gapped setups. Exact figures should be confirmed on the pricing page for current rates.

- **learner-1 memory model:** A dedicated model extracts, merges, infers and forgets across stored context so the memory graph keeps improving instead of simply accumulating.
- **Vector-graph memory store:** Learnings link to the entities, sources and moments around them, storing not just content but a time-aware map of how facts relate.
- **Model, harness and MCP agnostic:** Memory lives outside model providers and is used through APIs, SDKs, plugins and MCP, so context carries across models and tools.
- **Real-time context injection:** Relevant memories are injected as tokens into the prompt at request time, giving agents relevant context without unbounded transcripts.
- **Enterprise deployment and compliance:** SOC 2 Type II, HIPAA BAA on higher tiers, GDPR compliance, plus deployment in the cloud, your VPC, your data center or air-gapped.

**Strengths:** Memory is decoupled from model providers, so accumulated context survives model swaps; Rich engineering evidence, including published benchmarks, latency figures and cost comparisons; Multiple integration surfaces — REST API, SDKs, plugins and MCP; Strong enterprise posture with SOC 2 Type II, HIPAA BAA, GDPR and air-gapped deployment options

**Limitations:** Self-serve pricing on the public site is thin, and exact tier costs may require a sales conversation; It is infrastructure rather than an end-user app, so there is real integration work before you see value; Benchmark results and adoption figures are vendor-reported and worth validating against your own workload

[Profile (Markdown)](https://openaitools.app/tool/supermemory-1.md)

## TiDB Cloud

TiDB Cloud is the managed service for TiDB, the open-source distributed SQL database created by PingCAP. It is designed for teams that have outgrown a single MySQL instance but do not want to rewrite their application or hand-shard their data. Because it speaks the MySQL protocol, existing drivers, ORMs and tooling generally continue to work, while the underlying storage is distributed across nodes so capacity grows horizontally rather than vertically.

The distinguishing feature is HTAP: the same cluster serves transactional workloads and analytical queries. That means live dashboards and real-time reporting can read from operational data without a separate ETL pipeline or a second analytical database to keep in sync. On top of the SQL engine, TiDB Cloud adds vector data types and vector indexes, so AI and retrieval-augmented generation workloads can store and search embeddings in the same database that holds application records.

Operationally, TiDB Cloud handles provisioning, upgrades, backups and scaling. You can create a MySQL-compatible cluster in minutes and deploy it in more than 30 regions across Amazon Web Services, Google Cloud, Microsoft Azure and Alibaba Cloud, keeping data close to users or inside a required jurisdiction. Security and compliance coverage includes SOC 1 Type 2, SOC 2 Type 2, SOC 3, ISO 27001, ISO 27701, PCI DSS, GDPR and HIPAA, which makes the service viable for regulated industries. Pricing for larger deployments is quote-based, so verify current rates with the vendor before committing to a budget.

**Pricing & Plans:** TiDB Cloud offers a free starting tier and usage-based options for smaller deployments, while Dedicated and Enterprise clusters are priced on request according to cluster size, regions and support level. Since published rates vary by workload and region, treat it as contact-for-pricing and confirm current numbers with PingCAP before planning a budget.

- **Elastic Horizontal Scaling:** Storage and compute scale up or down in seconds without downtime or manual sharding, letting applications handle spikes and growth while paying for the capacity they use.
- **Enterprise-Grade Security & Compliance:** TiDB Cloud meets SOC 1 Type 2, SOC 2 Type 2, SOC 3, ISO 27001, ISO 27701, PCI DSS, GDPR and HIPAA standards, with encryption and access controls suitable for regulated workloads.
- **High Availability by Design:** Distributed transactions and multi-replica Raft consensus keep the database available through node and zone failures, and clusters can span availability zones or regions for disaster recovery.
- **HTAP: OLTP and Analytics Together:** One engine handles transactional and analytical queries, so you can run real-time reporting and analytics directly on live operational data instead of maintaining a separate warehouse pipeline.
- **MySQL Compatibility & Vector Search:** Vector data types and indexes support embedding storage and similarity search for AI and RAG applications, with standard MySQL-compatible interfaces for existing drivers and tools.

**Strengths:** MySQL wire compatibility that lets most existing applications, drivers and ORMs connect with minimal changes; Elastic scaling of storage and compute without downtime, manual sharding or application rewrites; HTAP engine runs transactional and analytical queries on the same live data; Available in 30+ regions across AWS, Google Cloud, Azure and Alibaba Cloud

**Limitations:** No public price list — you must request a quote for Dedicated and Enterprise, which slows evaluation; Distributed SQL is architecturally more complex than a single-node MySQL setup, so some tuning concepts are new to teams; Self-managed TiDB requires Kubernetes and operational expertise, while TiDB Cloud is the managed path; Full compliance documentation and enterprise features are aimed at larger organizations rather than hobby projects

[Profile (Markdown)](https://openaitools.app/tool/tidb.md)

## Frequently Asked Questions

### How do supermemory and TiDB Cloud compare in monthly traffic?

supermemory has 156,579 monthly visits, while TiDB Cloud has 61,010. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

supermemory has a month-over-month growth rate of -7.7%; TiDB Cloud has -17.9%.

### How does pricing compare?

supermemory: Contact for Pricing. Pricing is split between self-serve tiers and enterprise contracts, which is why the site lists a contact-for-pricing model. Free, Pro and Max tiers cover standard PDF extraction and personal use, while Scale and Enterprise add advanced document extraction with OCR and figure/diagram descriptions, higher limits, security guarantees such as SOC 2 Type II and HIPAA BAA, and deployment choices including your VPC, your data center or air-gapped setups. Exact figures should be confirmed on the pricing page for current rates. TiDB Cloud: Contact for Pricing. TiDB Cloud offers a free starting tier and usage-based options for smaller deployments, while Dedicated and Enterprise clusters are priced on request according to cluster size, regions and support level. Since published rates vary by workload and region, treat it as contact-for-pricing and confirm current numbers with PingCAP before planning a budget.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Composio](https://openaitools.app/tool/composio) | 2,782,603 | +22.8% | Freemium, Contact for Pricing | Focuses on tool integrations and authentication for agents, complementing memory engines rather than storing cross-session context. | [.md](https://openaitools.app/tool/composio.md) |
| 2 | [Salad](https://openaitools.app/tool/salad-gpu-cloud) | 713,519 | +10.4% | Free Trial, Paid, Contact for Pricing | Distributed GPU cloud that orchestrates the world's idle consumer GPUs | [.md](https://openaitools.app/tool/salad-gpu-cloud.md) |
| 3 | [LiteLLM](https://openaitools.app/tool/litellm) | 576,967 | +7.9% | Freemium, Contact for Pricing | One open-source AI gateway for 100+ LLM providers | [.md](https://openaitools.app/tool/litellm.md) |
| 4 | [Merge](https://openaitools.app/tool/merge-dev) | 313,201 | +1.7% | Freemium, Contact for Pricing | The universal context engine connecting agents to data, tools, and models | [.md](https://openaitools.app/tool/merge-dev.md) |
| 5 | [Pinecone](https://openaitools.app/tool/pinecone) | 286,732 | -31% | Freemium, Paid, Contact for Pricing | The managed vector database and knowledge engine for production AI | [.md](https://openaitools.app/tool/pinecone.md) |
| 6 | [Portkey](https://openaitools.app/tool/portkey-ai) | 195,650 | -9.4% | Freemium, Paid, Contact for Pricing | AI gateway, observability and guardrails for production LLM apps | [.md](https://openaitools.app/tool/portkey-ai.md) |
| 7 | [Honcho](https://openaitools.app/tool/honcho) | 137,752 | +2.2% | Paid, Contact for Pricing | Provides open-source persistent user modelling for stateful agents, but focuses more on conversational psychology than universal vector graphs. | [.md](https://openaitools.app/tool/honcho.md) |
| 8 | [Zilliz](https://openaitools.app/tool/zilliz) | 108,886 | -16.4% | Freemium, Paid, Free, Contact for Pricing | Fully managed Vector Lakebase and vector database for enterprise AI, built by the creators of Milvus | [.md](https://openaitools.app/tool/zilliz.md) |
| 9 | [LokiProxy](https://openaitools.app/tool/lokiproxy) | 94,819 | +40.3% | Free Trial, Paid, Contact for Pricing | Residential, mobile and IPv6 proxy network for large-scale data collection | [.md](https://openaitools.app/tool/lokiproxy.md) |
| 10 | [GreenNode](https://openaitools.app/tool/greennode) | 75,996 | +28.1% | Paid | Sovereign, high-performance AI cloud built in Southeast Asia | [.md](https://openaitools.app/tool/greennode.md) |

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Source: https://openaitools.app/compare/supermemory-1-vs-tidb

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