Data and AI platforms / Eventual alternative

Eventual.ai alternative

Eventual’s current site focuses on data curation for physical AI: extracting actions, interactions, trajectories and quality signals from video and telemetry. Its related Daft site describes an open-source multimodal data engine. Compare those data-product requirements separately from an agent’s returning Linux environment.

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Reviewed 2026-10-18 · Published by the Sandbox0 team

When Eventual fits

Eventual fits teams curating robotics/video/sensor training data and evaluating the quality of extracted signals. Daft can serve multimodal CPU/GPU pipelines. Preserve those data-processing capabilities when they are the workload’s central value.

When to consider Sandbox0

Consider Sandbox0 when the needed layer is a durable Linux computer for an agent’s tools, configuration and growing files. You still choose and run or integrate the data engine, curation models, data storage and any specialized accelerator infrastructure.

Capabilities

Eventual and Sandbox0: what persists?

Feature comparison with documentation and verification status
Environment and runtime lifetimeEventualNot established in this reviewSandbox0ttl and hard_ttl default to 0 (disabled). Configure idle pause and deletion policies for the same persistent sandbox identity; an idle running sandbox still accrues compute charges.Read documentation →
Persistent filesEventualVersioned curation outputs/datasets are described; a generic durable execution-disk contract is not established.View evidence ↗Sandbox0The writable RootFS survives successful checkpoints, including software, system configuration, dependencies, and user data.Read documentation →
Whole RootFSEventualA data engine and dataset storage do not establish complete writable Linux RootFS retention.View evidence ↗Sandbox0Persistence extends beyond /workspace to paths such as /usr/local, /etc, and /home. Runtime tmpfs and virtual filesystems are excluded.Read documentation →
Release compute, keep stateEventualDataset pipeline state is not an established arbitrary-process pause/resume interface.View evidence ↗Sandbox0Pause compute between tasks; resume on available capacity. Default resume starts fresh processes from the saved filesystem.Read documentation →
Memory and process stateEventualNo arbitrary process-memory snapshot contract is established.View evidence ↗Sandbox0Experimental memory checkpoints can preserve compatible process state. Use memory: true on both pause and resume on a compatible deployment. A filesystem checkpoint alone does not preserve running processes.Read documentation →

Online RootFS growth

On growth-enabled images, Sandbox0 automatically expands the writable RootFS as free space runs low, within a configured sparse logical ceiling up to 64 TiB. Agent processes keep running. Growth is enabled in the qualified Cloud region; confirm activation for other regions. Existing images and snapshots retain their captured storage geometry. The ceiling is logical capacity, not preallocated host disk.

Eventual’s retained curation outputs and Daft’s scalable data pipelines are acknowledged. Pipeline parallelism and external datasets have different ownership from a complete durable agent RootFS that expands online as installed tools and local files grow.

Files while compute is paused

Sandbox0's Files API reads persistent files without resuming compute. Filesystem-only pauses also permit edits; retained-memory pauses are read-only and reject mutations with 409. SSH, SFTP, file watching, and runtime-only mounts require running compute.

Access to stored datasets or curation results can be separate from compute, but that does not establish a full paused-RootFS file interface. The reviewed current Eventual/Daft sites do not define that machine-level contract.

See paused file operations →

Curation signals and versioned datasets are the product

The homepage describes understanding video/telemetry, searching behaviors and selecting reliable training examples, with signals versioned alongside data releases. That is valuable retained application data. It does not establish a customer-controlled full Linux RootFS or arbitrary process-memory checkpoint.

Source 1 ↗

Daft is a separate data-engine surface

The Daft site describes multimodal dataframe operations, CPU/GPU scheduling and batching, with source and documentation links. The company’s curation offer and an open-source execution engine are not interchangeable commercial units. Installing a library does not allocate durable hosted compute for free.

Source 1 ↗Source 2 ↗

Evaluate the actual pipeline rather than a generic VM rate

The current public sites offer a demo/contact path without a numeric self-service curation or universal compute tariff. Scope the data volume, models, hardware, storage and service responsibilities in the quote. A vendor benchmark on a fixed dataset is not a throughput or quality guarantee for your own pipeline.

Source 1 ↗Source 2 ↗

Pricing

Compare billing models, then price your workload

CPU allocation, memory, billing minimums, disk, plan fees, and supported workload differ. These meters are not equal-performance machine quotes. Confirm region, resource units, and included allowances before estimating a total.

Eventual

Pricing reviewed 2026-10-18

Eventual data curation
Vendor quote required
Scope datasets, signals, pipeline integration and service responsibilities.
Rate source ↗
Daft engine
Open-source software with separate execution costs
Software availability does not make CPU/GPU, storage or a managed service free.
Rate source ↗

This page follows Eventual’s current physical-AI curation scope and distinguishes the related Daft engine. It does not infer a shutdown date or an old cloud-compute plan from a product-name change. No data-quality benchmark, GPU availability or cost equivalence with Sandbox0 is asserted.

Check current Eventual pricing ↗

Sandbox0

$0.015/GiB-hour compute (billed by the second at approximately $0.000004167/GiB-second), plus $0.02/GiB-month of retained incremental RootFS and memory checkpoint data. Shared base images and platform recovery retention are excluded; paused sandboxes accrue storage charges only.

Compute / GiB-hour
$0.015
Retained data / GiB-month
$0.02
Paused compute
$0.00

A 4 GiB agent, 100 running hours

$6.00 compute

4 GiB × 100 hours, billed by the second. Keeping 20 GiB of billable incremental data for a full billing month adds $0.40. CPU is derived from memory by the platform; choose a tier that fits your workload.

Understand storage billing →

Before migrating from Eventual

  1. Identify curation service versus Daft engine, source data, model/hardware needs, versioned outputs and effective commercial scope.
  2. Use Sandbox0 for compatible agent tooling while retaining an appropriate data engine, storage and accelerator backend.
  3. Test package/configuration retention, growing outputs, paused files and complete curation/runtime/storage/model costs.

Common questions

Is Sandbox0 a drop-in Eventual replacement?

Evaluate API compatibility and product scope. These products serve different core workflows, so a change may require a different architecture.

Does keeping files also keep a running agent?

Filesystem state and volatile process state are separate. Sandbox0 requires explicit compatible memory checkpoints to preserve running processes; its default filesystem resume starts fresh processes.

Sources and review scope

The Boat team's Battleships directory is the discovery source. References below describe the product and plan discussed on this page. Check current availability, regional terms and billing units before migrating. Where the cited material does not establish a capability or price, the comparison identifies that uncertainty.

Battleships research record ↗www.eventual.ai/ ↗www.daft.ai/ ↗www.daft.ai/llms.txt ↗Sandbox0 RootFS capacity →

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