| Dimension | LlamaIndex | Akka |
|---|---|---|
| What it is | A RAG / data framework for indexing and retrieval (plus LlamaCloud, a managed parsing/indexing service) | A full-stack agentic systems platform |
| Primary job | Connect, parse, index, and retrieve your data so an LLM has the right context | Run, scale, persist, and govern agentic systems in production |
| Agentic features | Workflows (event-driven orchestration), function-calling and ReAct agents, AgentWorkflow — a library you deploy and operate | Native agents, durable memory, streaming, APIs, orchestration, and governance on one runtime |
| Durable execution | Not built in — Workflows do not auto-checkpoint; durability needs an external integration (e.g., DBOS), replay-based and at-least-once | Durable sharded in-memory state, event-sourced, replayable; 4ms reads / sub-10ms writes |
| Availability SLA | No published numeric SLA; "uptime SLAs" referenced for the enterprise tier only | 99.9999% — entire platform, backed by indemnities |
| HA/DR | Customer-owned (self-hosted) or per managed-service terms; no published active-active / RTO / RPO | Active-active across regions; sub-1-minute RTO; zero-byte RPO |
| Governance / EU AI Act | Observability and evaluation integrations; no inline enforcement, immutable ledger, pre-deployment classification, or sealed artifact | Aspect-woven runtime enforcement + full pre-production governance |
| Cost model | Consumption credits ($1 / 1,000 credits; ~3 credits/page; 10,000 free credits/mo) + you provision and operate everything else | Shared compute; up to 90% lower infrastructure for the same workload, fixed annual fee |
| Certifications | SOC 2 Type II reported for LlamaCloud | 19 standards (SOC 2 II + public SOC 3, ISO 27001/42001, HIPAA, PCI DSS, GDPR, NIS2, DORA, EU AI Act, NIST AI RMF) |
| Vendor model | Venture-funded: $19M Series A (Mar 2025), ~$93M post-money; Databricks & KPMG strategic minority investments | Profitable and self-funding; 18 years, 100,000+ deployments; Dell Technologies Capital is largest shareholder, customer, and AI partner |
LlamaIndex is a data framework for retrieval-augmented generation: data connectors, document parsing (LlamaParse), indexing, and query/retrieval interfaces that give a model the right context. It does this well, and it has added agentic constructs — Workflows (event-driven orchestration), function-calling and ReAct agents, and AgentWorkflow. Those are libraries you import, deploy, and operate. The substrate a production agentic system runs on — a durable runtime, high availability, disaster recovery, and embedded governance — is not part of LlamaIndex; you build, integrate, and operate it yourself, and own every failure across the seams.
| Capability | LlamaIndex | Akka |
|---|---|---|
| Data ingestion, parsing, indexing, retrieval (RAG) | Yes — its core strength | Not native (see complement note) |
| Agent constructs (tools, function calling, ReAct) | Library | Built in |
| Event-driven orchestration (Workflows) | Library | Built in |
| Durable execution / crash recovery | External integration (e.g., DBOS) | Built into the runtime |
| Durable memory | Bolt-on store | Built in, 4ms / sub-10ms |
| Real-time streaming | None native | Built in, backpressured, petabyte-scale |
| HTTP / gRPC API layer | None | Built in |
| Runtime governance / policy enforcement | None | Inline, runtime-embedded |
| Pre-production governance | None | Classification, sign-offs, sealed posture |
LlamaIndex does not publish a numeric availability SLA; "uptime SLAs" are referenced only generically for the enterprise tier, with no stated percentage, RTO, or RPO. More important for agentic AI is durable execution. LlamaIndex Workflows do not automatically snapshot state — by design, to avoid overhead — so a workflow cannot recover from a crash on its own. Durable execution is available only through an external integration such as DBOS, which journals step completions to a database and replays on restart; recovery is at-least-once, so steps can run more than once and the developer must make them idempotent.
| Metric | LlamaIndex | Akka |
|---|---|---|
| Availability SLA | None published (numeric) | 99.9999% |
| Allowed downtime / year | Not specified | ~31 seconds |
| Durable state | External integration; replay-based, at-least-once | Event-sourced, built in; exactly-once recovery |
| State latency | Per external store | 4ms reads / sub-10ms writes |
| RTO / RPO | Not published | Sub-1-minute RTO / zero-byte RPO |
| HA/DR | Customer-owned / per managed terms | Active-active across regions |
| SLA scope | — | The entire platform, backed by indemnities |
Akka provides durability and fault tolerance as part of the runtime: state is event-sourced in durable sharded in-memory storage, replayable from its own journal, with active-active HA/DR, sub-1-minute RTO, and zero-byte RPO under a 99.9999% SLA. Eighteen years and 100,000+ production deployments stand behind it.
AI systems built with Akka are up to 90% cheaper to operate than Python-based systems — a function of the infrastructure required for the same agentic transaction volume, not list price. The drivers are actor concurrency (~10 trillion tokens/core/year vs ~2 trillion for comparable solutions; ~80% less compute than Python-based frameworks), shared compute, and micro-checkpointing. Manulife reported up to 300% more concurrency and 30–50% faster processing after porting Python-based systems to Akka.
LlamaCloud bills by consumption — $1 per 1,000 credits, roughly 3 credits per page for cost-effective parsing, with 10,000 free credits per month — and that meter covers parsing, extraction, and indexing: the retrieval layer. The runtime to run agents in production (compute, memory, streaming, APIs, observability, governance, HA/DR) is provisioned and paid for separately, on top. Akka runs all of it on one shared-compute runtime for a fixed annual fee finance can forecast.
LlamaIndex provides observability and evaluation: instrumentation, tracing integrations, and evaluation tooling to measure retrieval and agent quality. It does not provide AI-governance enforcement — no real-time policy enforcement, no decision explainability, no human pause/override of a running process, no immutable interaction ledger, no pre-deployment classification, and no sealed audit artifact.
| Violation | Maximum Fine |
|---|---|
| Prohibited AI practices (Art. 5) | EUR 35M or 7% global turnover |
| High-risk obligations (Art. 9-15) | EUR 15M or 3% global turnover |
High-risk AI carries a 10-year logging-retention obligation (Art. 72), enforceable since Feb 2025 (prohibited) / Aug 2025 (high-risk).
At the runtime: inline guardrails, policies, LLMs-as-a-judge, and sanitizers; hash-chained immutable evidence; HITL/HOTL human control; atomic PII scrub-with-explain; pre-deployment classification against 189 regulations and 962 controls (574 carrying a financial penalty); multi-persona sign-offs; a sealed Governance Posture Package; and Akka Verify proving conformance from the running system. Governance that LlamaIndex would leave a customer to source and bolt on, Akka enforces inline.
Building on LlamaIndex means engineers writing retrieval and workflow code; there is no built-in path for a risk officer or compliance lead to contribute, and no governance lifecycle. Akka runs two independent lifecycles on one platform via Akka Specify:
The build lifecycle and the governance lifecycle are versioned and tested independently, by different audiences — an audience and a workflow LlamaIndex has no equivalent for.
LlamaIndex has no streaming engine; real-time pipelines are provisioned separately. Akka's streaming is built into the runtime — continuous, backpressured, petabyte-scale, in-memory, with no external broker — powering both agent feedback loops and high-throughput data processing (the engine behind Tubi's real-time hyper-personalization at 5 billion tokens per second).
| Buyer concern | LlamaIndex | Akka |
|---|---|---|
| Certifications & audits | SOC 2 Type II reported for LlamaCloud | 19 standards — SOC 2 II + public SOC 3, ISO 27001/42001, HIPAA, PCI DSS, GDPR, NIS2, DORA, EU AI Act, NIST AI RMF — plus annual pen tests, SBOMs, 40+ policies (trust.akka.io) |
| Scope of accountability | The retrieval layer; you integrate and operate the runtime, agents, and governance | One platform, one SLA, 24/7 SRE — Akka owns the running system |
| Risk transfer | Standard cloud terms | Availability and data-integrity guarantees backed by contractual indemnities |
| Track record & funding model | Venture-funded: $19M Series A (Mar 2025), ~$93M post-money; Databricks and KPMG strategic minority investments | Profitable and self-funding; 18 years and 100,000+ deployments (52 banks); Dell Technologies Capital is largest shareholder, a customer, and an AI partner |
| Budget predictability | Consumption credits that scale with load | Fixed annual fee finance can forecast |
The decision is scope and accountability: LlamaIndex gives you a best-in-class retrieval layer to feed an agent; Akka gives you the platform that runs and guarantees the agent.
LlamaIndex product / RAG: llamaindex.ai · developers.llamaindex.ai/python/framework/ — open-source data framework for RAG (ingest, index, retrieve); "AI Agents for Document OCR + Workflows" (Jun 2026)
LlamaIndex agentic constructs: developers.llamaindex.ai/python/llamaagents/workflows/ — Workflows (event-driven), AgentWorkflow, function-calling / ReAct agents
Workflows durability: developers.llamaindex.ai/python/llamaagents/workflows/dbos/ — Workflows do not auto-snapshot; durable execution via DBOS journaling, replay-based, at-least-once (idempotency required) (2026)
LlamaCloud pricing: llamaindex.ai/pricing · developers.llamaindex.ai/python/cloud/general/pricing/ — $1 per 1,000 credits; ~3 credits/page (cost-effective); 10,000 free credits/month
LlamaIndex SLA / security: no published numeric availability SLA; "uptime SLAs" referenced for enterprise tier only; SOC 2 Type II reported for LlamaCloud
LlamaIndex funding: prnewswire.com / crunchbase.com — $19M Series A led by Norwest with Greylock, Mar 4 2025, ~$93M post-money, $27.5M total disclosed; Databricks Ventures + KPMG strategic minority investments (May 2025)
Akka trust center: trust.akka.io — 19 compliance standards; SOC 2 II + public SOC 3; annual pen tests, SBOMs, 40+ policies
Akka performance: akka.io/blog/go-slow-to-go-fast — Manulife up to 300% more concurrency, 30–50% faster; ~10T vs ~2T tokens/core; ~80% less compute than Python
Akka platform: 99.9999% availability, active-active HA/DR, sub-1-min RTO, zero-byte RPO (contractual indemnities); 4ms reads / sub-10ms writes; 189 regulations / 962 controls / 574 with a financial penalty; 100,000+ deployments / 18 years / 52 banks; profitable; Dell Technologies Capital
