Vedika vs RoxyAPI: Two Own-Engine Astrology APIs Compared (Honestly)

If you are evaluating astrology APIs as an engineer, the first filter that actually matters is not pricing or endpoint count — it is who owns the math. Nearly every astrology API on the market is a thin REST wrapper around the same C library: Swiss Ephemeris. Prokerala, AstrologyAPI.com, DivineAPI, FreeAstrologyAPI, and the popular Python libraries Kerykeion, flatlib, immanuel, and VedAstro all link it. That is a perfectly reasonable engineering choice — Swiss Ephemeris is superb — but it means those vendors inherit its AGPL-3.0 license obligations and depend on an upstream they do not control.

Exactly two API vendors broke from the pack and built their own ephemeris engine from scratch: RoxyAPI (Roxy Ephemeris, MIT-licensed, validated against JPL Horizons) and Vedika (XALEN, a pure-Rust Apache-2.0 engine). If your search query is "roxyapi alternative astrology api own engine," this is the honest answer: RoxyAPI is a genuine engine peer, not a wrapper. So the engine argument — the one Vedika uses to win against everyone else — is a draw here. This comparison drops it and looks at what actually differs.

The short answer

RoxyAPI and Vedika both own their ephemeris and both ship JPL-validated accuracy under permissive (non-AGPL) licenses. The difference is stack depth above the ephemeris. RoxyAPI gives you clean, fast astronomy and Western-leaning astrology primitives. Vedika layers a much wider divination stack on top — ~25 systems, deep Vedic computation (yogas, doshas, dashas, 36-guna matching, KP, Lal Kitab), a RAG-grounded conversational LLM endpoint, and native speech-to-LLM-to-speech voice in 30 languages with 30 languages platform-wide. Pick RoxyAPI if you want a lean astronomy/astrology primitive. Pick Vedika if you want a full product surface, especially with Vedic depth or conversational/voice features.

Why "own engine" is the right filter

Wrapping Swiss Ephemeris creates two structural liabilities that have nothing to do with code quality:

• License entanglement. Swiss Ephemeris is dual-licensed: AGPL-3.0 or a paid commercial license. Under AGPL §13, a networked SaaS that links the library must offer its complete corresponding source to remote users — unless it buys the commercial license. That commercial license is a legitimate path (a modest one-time fee with 99-year validity), and plenty of companies take it. But it is an upstream legal dependency you carry forever.
• Upstream control. When you wrap someone else's engine you do not control its release cadence, its build targets, or its future licensing. Owning the engine removes that risk entirely.

Both RoxyAPI and Vedika sidestep both liabilities. Roxy Ephemeris is MIT; XALEN is Apache-2.0. Neither imposes a copyleft source-disclosure obligation on you. If you are building a closed-source, white-label, or on-prem product, that freedom is the whole game — and it is the reason the "own engine" cohort is worth isolating in the first place.

Head-to-head comparison

Be clear about what this table does not say: it does not claim Vedika's astronomy is more accurate than RoxyAPI's. Both are own-engine, both are JPL-validated; on raw astronomy they are peers. Vedika's advantage is everything above the ephemeris line.

The accuracy framing (matches, does not "beat")

This is where most astrology marketing lies, so here are real, reproducible numbers and an honest ceiling.

XALEN was validated against NASA JPL DE440 over the 1900–2050 range. Mean angular error:

Every classical planet is sub-arcsecond. The analytic Moon model is arcsecond-class (a few arcseconds), which is wider — that is expected for a truncated analytic lunar theory. A 20,000-chart sweep across the 1900–2050 grid produced zero charts exceeding 0.1° (six arcminutes) of error, which is far inside the tolerance any astrological interpretation requires.

Now the guardrail, stated plainly: Swiss Ephemeris reproduces JPL to roughly one milliarcsecond and remains the reference implementation. XALEN matches Swiss/DE440 to JPL-class parity for the classical planets — it does not beat it, and its analytic Moon is wider. The correct claim is "sub-arcsecond agreement / JPL-class parity," never "more accurate than Swiss." If you need sub-arcsecond Moon and outer-planet precision, XALEN can load the JPL DE440 SPK kernel and read positions directly from it. RoxyAPI's accuracy story is comparable — own engine, JPL-validated — and the honest takeaway is that for the planets, all three (XALEN, Roxy, Swiss) are well within any tolerance astrology cares about. The accuracy debate is settled and uninteresting; the stack above it is where you should spend your evaluation time.

You do not have to take the numbers on faith. The XALEN validation harness is open and runnable:

cargo run -p xalen-validation

That regenerates the DE440 comparison against the published grid, which is the standard a skeptical engineer should hold any "own engine" vendor to — including RoxyAPI.

What XALEN actually is (so you can verify it)

XALEN is a pure-Rust ephemeris engine: VSOP87A series for the planets, a truncated ELP2000-82 theory for the Moon, Meeus algorithms, IAU 2006 precession with the 2000B nutation model, and an optional JPL DE440 SPK kernel reader for when you want JPL-grade output directly. The core is zero-unsafe, thread-safe, and compiles to wasm32. A full chart computes in roughly 336µs.

It is not a closed binary you have to trust — it is published. As of v0.6.0:

• crates.io — 15 crates including xalen-ephem, xalen-coords, xalen-houses, xalen-vedic, xalen-western, xalen-time, xalen-ayanamsa, xalen-stars, xalen-chart, xalen-chinese, xalen-world, xalen-lalkitab, xalen-iching, xalen-numerology, xalen-ffi
• npm — @xalen/wasm plus @vedika-io/sdk, @vedika-io/mcp-server (36 tools), @vedika-io/cli, @vedika-io/react
• PyPI — xalen 0.6.0 and vedika-sdk
• GitHub — vedika-io/xalen-ephemeris, Apache-2.0

These install cleanly today:

cargo add xalen-ephem
pip install xalen
npm i @xalen/wasm

The point of listing the registries is not bragging rights — it is that an "own engine" claim is only credible if you can cargo add it and run the validation yourself. Vedika passes that test; hold RoxyAPI to the same bar.

Where RoxyAPI is the better choice (giving credit honestly)

RoxyAPI earns its place, and pretending otherwise would make this comparison useless. If your needs are:

• Primarily Western/tropical astrology or raw astronomical positions;
• A lean, fast primitive you will compose into your own product logic;
• MIT licensing specifically (slightly more permissive than Apache-2.0 in that it has no explicit patent grant or attribution-on-modification clauses — a real preference for some teams);
• A free tier to prototype against before committing,

then RoxyAPI is an excellent fit and a legitimately strong engineering peer. You should benchmark both against your own chart fixtures rather than trusting any vendor's table — ours included.

Where Vedika pulls ahead

Vedika's bet is that most teams do not want to assemble an astrology product from astronomy primitives — they want the product surface ready. Concretely:

• Breadth. ~25 systems and 704 operations (around 250 exposed in the public sandbox), spanning Vedic, Western, KP, Chinese, numerology, Lal Kitab, I Ching, and more.
• Vedic depth. 104–131 computed yogas, doshas, Vimshottari and conditional dashas, 36-guna (Ashtakoot) matching, 60 divisional charts (D1-D60), 50 ayanamsas, and 23 house systems. A raw ephemeris — Swiss or Roxy — gives you positions; it does not give you any of this interpretive computation. You would have to build it.
• Conversational LLM, RAG-grounded. POST /api/v1/astrology/query answers natural-language questions grounded in retrieved classical sources rather than emitting free-form model text. This is a generated, retrieval-grounded answer, not a canned template.
• Native voice in 30 languages. A full speech-to-language-to-speech pipeline, not a TTS bolt-on — useful if you are building a voice assistant or IVR product.
• 30 platform languages and an MCP server (36 tools) for AI-agent integration, starting at $12/mo.

A useful way to frame it: Swiss Ephemeris (and any wrapper of it, and a raw own-engine like Roxy used at the primitive level) provides raw astronomy only — no yogas, no doshas, no dashas, no matching. Vedika ships the astronomy and the entire interpretive layer above it.

How to decide

Run this checklist against your actual project:

• Need Apache-2.0 or MIT, not AGPL, for a closed/white-label product? → Both RoxyAPI and Vedika qualify. Every Swiss-wrapping competitor does not (without the commercial license).
• Want a lean Western/astronomy primitive? → RoxyAPI.
• Want deep Vedic computation, conversational answers, or voice? → Vedika.
• Want to embed the engine itself in your binary/wasm bundle? → XALEN is the only one published across crates.io, npm, and PyPI for direct embedding.

The most honest recommendation is to benchmark both engines against your own chart fixtures and against DE440 before you commit a line of integration code. Then choose on stack depth, not on a marketing accuracy claim — because on accuracy, the own-engine cohort is already at parity with the reference.

Try it

You can probe Vedika without a key in the free sandbox, read the API reference, or install the engine directly. Start at vedika.io for the docs and sandbox, or run cargo add xalen-ephem / pip install xalen / npm i @xalen/wasm to validate the engine on your own machine first. Either way, verify before you trust — that is the entire point of choosing an own-engine vendor.