The Palantir Ontology alternative on the databases you already run
SynaLemma answers questions on your business data with rules that are proved before they run, then compiled to SQL on the databases you already run. No platform to adopt, no data to move.
SynaLemma vs Palantir Ontology: key differences
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On the databases you already run
Rules, recursive ones included, compile to SQL on PostgreSQL, BigQuery, Databricks, Trino, Presto, DuckDB and SQLite. No platform to adopt, no ETL, no data to move.
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Every rule proved before it runs
A symbolic verifier proves each rule well-formed, safe and terminating. An invalid rule is rejected with the reason, before any SQL runs.
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Assertions that name the faulty rows
Keys, references, totals or transitivity are written in first-order logic. The engine searches the whole table and returns the rows that break them.
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The agent never writes SQL
The agent writes rules, not SQL. The engine checks every rule, then writes SQL that only reads your tables: no raw SQL and no injection, formally proved.
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Same question, same SQL
The same question always compiles to the same SQL, and every figure cites the rule it came from. Your team can read, correct or lock that rule.
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Sovereign by construction, not by contract
Data, rules and model stay on your infrastructure. The engine compiles the SQL, so a small open model is enough, with no per-token fees. The Synalog engine is open source, under Apache-2.0.
Example: a recursive query with assertions
A bill of materials at any depth, with two assertions. The data contains a cycle; the engine reports it before any answer is returned.
# The bill of materials, read from the database.
Component(assembly:, part:, quantity:) :- bom(assembly:, part:, quantity:);
# A part is inside an assembly directly, or inside one of its parts.
@Recursive(Contains, 20);
@Assert(Contains,
transitive: "∀ a b c, Contains a b → Contains b c → Contains a c",
no_cycle: "∀ a, ¬ Contains a a");
Contains(assembly:, part:) distinct :- Component(assembly:, part:);
Contains(assembly:, part:) distinct :-
Contains(assembly:, part: sub),
Component(assembly: sub, part:); SynaLemma vs Palantir Ontology at a glance
| Criterion | SynaLemma | Palantir Ontology |
|---|---|---|
| How an agent answers | It writes a rule; the engine proves it and compiles the SQL | The model calls tools: object queries, functions and actions |
| What checks the definitions | Every rule proved well-formed, safe and terminating before it runs | Save-time checks; no formal verification documented |
| Checks on the data | Assertions in first-order logic that return the rows breaking them | Data expectations on pipeline outputs, pass or fail; no counterexamples documented |
| Hierarchies and multi-hop chains | Native recursion at any depth, verified to terminate | Search Around, one link at a time; no recursion documented |
| Definitions written in | Synalog, an open-source logic language with a compiler | Object and link types configured in Ontology Manager; functions in TypeScript |
| Where the data lives | Your databases, queried with compiled SQL | Object types indexed in Foundry, from datasets or virtual tables |
| Language model | The one you choose: a small open model is enough, no per-token fees | Palantir-provided models, or your own registered models |
| Deployment | On-premises, on your existing databases | Foundry, delivered by Apollo: cloud, on-premises or air-gapped |
Why teams look for a Palantir Ontology alternative
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A platform to adopt
Object types are indexed into Foundry, even when backed by a virtual table on an external source (virtual tables).
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No recursive traversal
Links are followed with Search Around, one link type per step; no recursive traversal is documented (link types).
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No formal verification
Ontology Manager blocks saves that contain errors; no check that definitions are well-formed or terminate is documented (saving changes).
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No counterexamples
Data expectations pass or fail a build; returning the rows that break them is not documented (data expectations).
Palantir Ontology alternative: FAQ
What is the best Palantir Ontology alternative for AI agents?
SynaLemma. It gives agents a verified model of the business on the SQL databases you already run: no platform to adopt, no data to move. Every rule is proved before it runs, and assertions name the faulty rows.
How does Palantir follow a hierarchy?
With Search Around, one link type per step; no recursive traversal is documented. In Synalog, recursion follows a hierarchy to any depth and is verified to terminate.
Do I need to move my data to use SynaLemma?
No. Synalog rules compile to SQL that runs on your existing databases.
Can SynaLemma run with a local model?
Yes. A small open model on your own hardware is enough, because the engine compiles the SQL.
Sources
- Palantir docs: link types
- Palantir docs: saving Ontology changes
- Palantir docs: data expectations
- Palantir docs: virtual tables
- Palantir docs: Chatbot Studio tools
- Palantir docs: AIP features
- Palantir docs: bring your own model
- Palantir docs: object types
- Palantir docs: Apollo
- Synalog on GitHub (Apache-2.0)
Checked against each product's public documentation on the review date. To report an error: contact@synalinks.com.
Other comparisons
Bring a question your current stack can't answer.
In 30 minutes, we show SynaLemma answering it, with the rule behind the number and the checks it passed.