Google AI ModeOct 3, 2026
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Data as of Oct 11, 2026A topic in AI Knowledge Graph Platforms.
Reviewed by Dimitry Apollonsky
Google AI ModeOct 3, 2026
When exploring fully managed knowledge graph and graph database services with a "forever-free" tier or significant experimental caps, a few robust options stand out . They balance zero-ops cloud management with limits generous enough to prototype real applications, run small-to-medium GraphRAG pipelines, or evaluate enterprise semantics.
db.t3.medium or db.t4g.medium instance, 10 million I/O requests, and 1 GB of storage/backup.If you'd like to narrow this down, tell me:
I can help you pick the best fit or map out a quick starter schema.
ChatGPT SearchOct 3, 2026
Yes. If by managed knowledge graph you mean a hosted service where you can experiment without running the database yourself, the strongest current options I found are:
| Service | Free experimentation | Main cap | KG model / query | Best fit |
|---|---|---|---|---|
| Neo4j AuraDB Free | Free forever | 200k nodes + 400k relationships, 1 DB | Property graph / Cypher | General-purpose KG, GraphRAG, developer experimentation |
ChatGPT SearchOct 4, 2026
Yes. For managed knowledge-graph experimentation, the free options are surprisingly uneven. The strongest choices I found are:
| Service | Free allowance | Managed? | KG / semantic features | My take |
|---|---|---|---|---|
| Neo4j AuraDB Free | 200k nodes / 400k relationships, 1 database, forever | ✅ | Property graph, Cypher, GraphQL, vector search, visualization | ⭐ Best general-purpose choice |
Google AI ModeOct 4, 2026
ChatGPT SearchOct 11, 2026
Yes. There are a few managed graph database services worth considering, but the key distinction is between a generous free tier that lasts indefinitely and a high-capacity trial that expires after a few days or weeks.
For experimenting with substantial datasets, lots of queries, graph algorithms, or an AI-powered knowledge graph, I'd start by comparing Neo4j AuraDB, Memgraph Cloud, and FalkorDB Cloud. Their free offerings differ considerably in resource limits, persistence, and how much traffic you can generate.
(Best free-forever starting point)
Fully managed · Cypher · AWS, Azure, Google Cloud
Google AI ModeOct 11, 2026
| Stardog Cloud | Free | 1M edges, 3 databases | RDF / SPARQL + reasoning | Semantic/OWL knowledge graphs |
| Memgraph Cloud | Free trial | 2 GB RAM, 1 project, 14 days | Property graph / Cypher | Graph analytics and application prototypes |
| Amazon Neptunehttps://aws.amazon.com/neptune/ | AWS Free Tier for qualifying accounts | Historically 750 instance-hours/month for eligible accounts | RDF/SPARQL + property graph APIs | AWS-centric experimentation |
| GraphDB Free | Free software rather than managed SaaS | 2 concurrent queries | RDF / SPARQL / OWL reasoning | Semantic KG experimentation, if self-hosting is acceptable |
Neo4j currently offers AuraDB Free at $0 forever, with no credit card required. The current limit is 200,000 nodes and 400,000 relationships in a single database. It's fully managed and supports Cypher, the Neo4j Browser, and the broader Neo4j tooling ecosystem.
Why I'd consider it: 400k relationships is a reasonably substantial graph for experimentation, and the free tier isn't merely a short-lived trial.
Stardog is more explicitly a knowledge-graph/semantic-data platform than Neo4j. Its current free Cloud plan allows up to 1 million stored edges and 3 databases, with shared hosting and community support.
This is the one I'd investigate if you specifically need RDF, SPARQL, ontology modeling, inference, or semantic reasoning rather than simply storing connected entities.
Memgraph offers a fully managed Cloud service, but its free allowance is a 14-day trial with one project using up to 2 GB RAM. After that, the project becomes paid.
Its underlying graph engine is Cypher-compatible and includes graph algorithms, vector search, and integrations useful for AI/GraphRAG experiments.
So I'd put it behind AuraDB/Stardog if your requirement is specifically "free for a long-running experiment."
Amazon Web Services's Amazon Neptune is a serious managed option supporting both RDF/SPARQL and property-graph workloads. AWS documents 750 free hours of entry-level Neptune instance usage for AWS accounts created before July 15, 2025.
That makes Neptune interesting for AWS users, but I wouldn't choose it specifically for a new long-lived free experiment without checking the exact Free Tier eligibility of your AWS account.
Ontotext's GraphDB Free is worth mentioning because its capacity model is unusually generous: current documentation says it can handle very large RDF datasets and supports full SPARQL, inference, etc., with two concurrent queries as the principal free-tier restriction.
The catch is important: it's software you run yourself, not a managed hosted service. Starting with GraphDB 11, you also need to request a free license.
If your requirement is specifically "managed + genuinely free + enough capacity to build something meaningful", I'd narrow it to:
One important distinction: Neo4j/Memgraph are primarily property-graph systems, while Stardog/GraphDB are much more naturally suited to RDF/OWL semantic knowledge graphs. If you're building a KG for GraphRAG, the choice between those two families can matter more than the raw free-tier size.
If you tell me whether you're after GraphRAG/LLM context, RDF/OWL semantics, or a general entity-relation store, I can also compare these on API access, vector search, embeddings, SPARQL/Cypher, inference, rate limits, and free-tier storage.
| 1 million edges |
| ✅ |
| RDF, SPARQL, reasoning, semantic KG tooling |
| ⭐ Best semantic/RDF choice |
| Amazon Web Services Neptune | 750 instance-hours on eligible new AWS accounts | ✅ | RDF/SPARQL + property graph/Gremlin/openCypher | Good for testing AWS-native architectures |
| GraphDB | Free edition; effectively unlimited RDF statements, but only 2 concurrent queries | ❌ for the free edition | RDF, SPARQL, RDFS/OWL reasoning, GeoSPARQL | Excellent KG engine, but not managed on its free tier |
Neo4j AuraDB Free is genuinely free forever, requires no credit card, and is fully managed. Current Neo4j documentation says the free instance supports up to 200,000 nodes and 400,000 relationships. It also includes the core graph tooling and visualization.
That's enough room for substantial experiments—for example, ingesting a moderately sized entity graph, experimenting with GraphRAG, testing Cypher queries, and building an application against it.
Caveat: the free database can auto-pause after three days of inactivity, and backups aren't included.
Stardog Cloud offers a free managed environment with up to 1 million stored edges. Stardog is much more explicitly oriented toward semantic knowledge graphs than a conventional property-graph database: RDF, ontologies, reasoning, and semantic querying are central to the product.
For your use case, I'd put this near the top if you're specifically experimenting with:
The free environment is shared cloud hosting with community support.
Amazon Neptune documentation currently describes 750 free instance-hours for eligible new AWS accounts, using t3.medium or t4g.medium instances.
That's potentially enough to run a small experiment continuously for roughly a month, but it's fundamentally different from AuraDB/Stardog's persistent free tiers: once the free allowance is exhausted, Neptune becomes billable.
It's nevertheless worth testing if you care about AWS integration or want to compare SPARQL/RDF vs. property-graph workloads in a managed hyperscaler environment.
GraphDB is worth mentioning because its free edition is unusually generous. Current documentation describes unlimited RDF statements, full SPARQL 1.1, RDFS/OWL reasoning, GeoSPARQL, etc., with a limit of two concurrent queries.
The catch is important: GraphDB Free is on-prem/self-managed; the managed service is an Enterprise offering.
There is also a current GraphDB Managed Evaluation offering through Microsoft's marketplace that supports up to 750 million RDF triples for six months, after which it moves to a limited free version. That's an unusually large managed evaluation allowance if six months is sufficient for your experiment.
If your goal is to experiment rather than immediately choose a production platform, I'd run the same small KG through these three:
Stardog → Neo4j → Neptune
They give you substantially different approaches:
And I'd add GraphDB if semantic reasoning is central to the experiment, despite the lack of a permanently managed free tier.
One particularly useful benchmark would be to load the same 100k–500k entity/relation dataset into Stardog and Neo4j and compare ingestion, traversal, SPARQL/Cypher expressiveness, reasoning, vector/LLM integration, and operational experience.
Here are fully managed graph services and database platforms that offer generous, permanent, or trial free tiers suitable for experimenting with knowledge graphs:
db.t3.medium or db.t4g.medium instance, 10 million I/O requests, 1 GB of storage, and 1 GB of backup storage.If you want to narrow this down, let me know:
I can recommend the best fit for your specific experiment.
Links: Free tier · Pricing and limits.
(Best for a short, intensive trial)
Fully managed · Cypher-compatible · AWS
Its pricing page advertises a separate 30-day Enterprise trial; check the eligibility and terms for that offer.
Links: Memgraph Cloud · Pricing.
Managed graph database · RedisGraph-compatible query model
The provider's public pricing page doesn't clearly specify a generous compute or query quota, so verify the actual free allocation before committing.
Links: FalkorDB pricing and plans.
A major caveat: a free tier with a large graph isn't necessarily a free tier with unlimited queries. Providers may impose memory, request-rate, inactivity, or runtime limits even if they don't charge per query.
Here is how I'd choose:
| Your priority | Best starting choice |
|---|---|
| Free indefinitely, conventional graph development | Neo4j AuraDB Free |
| High-memory experimentation for a limited time | Memgraph Cloud |
| Multiple lightweight graphs and an MVP | FalkorDB Cloud |
| Heavy workloads with no query-based fees | Memgraph Community Edition, self-hosted |
For a larger Neo4j experiment, there's also a $150 credit, 14-day managed trial for paid AuraDB tiers, with a maximum 4 GB instance during the trial. That's a more useful option for testing a larger workload than the free tier, although it isn't a permanent free service.
When you say “high usage limits,” which constraint matters most?
1. What do you need most?
Lots of queries / API requests
Large graph size (millions of nodes or more)
High CPU/RAM for algorithms and traversals
Always-on hosting without inactivity pauses
2. Must it be fully managed?
Yes, hosted by the provider
Self-hosting is fine if it is free
Either is fine
3. Roughly how big is your graph?
Under 100,000 nodes
100,000 to 1 million nodes
Millions of nodes or more
Not sure yet
[Find the best match]
No major fully managed graph database provider offers a truly free tier with high usage limits , as graph processing and memory consumption are resource-intensive. Most managed services cap their free tiers strictly for prototyping, education, or small-scale evaluation.[](https://support.neo4j.com/s/article/16094506528787-Support-resources-and-FAQ-for-Aura-Free-Tier)[[2](https://neo4j.com/pricing)](https://neo4j.com/pricing/)
db.t3.medium or db.t4g.medium instance), rather than a permanent free tier.If you need high usage limits for experimentation without paying for a managed cloud tier, your best option is running an enterprise-grade graph database locally or on a cheap cloud VPS using Docker:
If you can share your expected data size (node/edge count) and query performance needs , I can help you decide whether a local Docker container or a paid cloud tier makes the most sense.