Development environments / Datalayer Runtimes alternative

A Datalayer Runtimes alternative for the persistent machine underneath an agent

Datalayer connects notebooks, agent workflows and code execution across several providers. Its own cloud runtime is one backend among local Jupyter, Docker and external sandbox services. Compare the selected backend with a persistent Linux computer rather than assume every Datalayer code sandbox has identical isolation, storage or process-state behavior.

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

When Datalayer Runtimes fits

Datalayer fits notebook and agent products needing provider selection, data access, codemode, governed tools and integrated interfaces. Keep these workflow functions when choosing a different machine runtime; changing an execution provider is an adapter and compatibility project.

When to consider Sandbox0

Consider Sandbox0 for compatible Linux execution with complete writable-RootFS persistence, automatic online growth and supported paused file operations. Retain or implement the notebook, agent specification, data connectors and governance layers the application requires.

Capabilities

Datalayer Runtimes and Sandbox0: what persists?

Feature comparison with documentation and verification status
Environment and runtime lifetimeDatalayer RuntimesServer-side execution is independent of the browser, but a runtime reservation still bounds the purchased running interval.View evidence ↗Sandbox0ttl 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 filesDatalayer RuntimesPersistent contents and provider storage have different contracts; no uniform retained machine disk is established for every provider.View evidence ↗Sandbox0The writable RootFS survives successful checkpoints, including software, system configuration, dependencies, and user data.Read documentation →
Whole RootFSDatalayer RuntimesContent mounts and notebook continuity do not establish a complete persistent writable RootFS across all backends.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 stateDatalayer RuntimesRuntime lifecycle varies by provider; there is no verified uniform complete-machine pause/resume contract here.View evidence ↗Sandbox0Pause compute between tasks; resume on available capacity. Default resume starts fresh processes from the saved filesystem.Read documentation →
Memory and process stateDatalayer RuntimesThe provider abstraction does not establish a universal arbitrary RAM/process snapshot guarantee.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.

Datalayer can attach content to its own runtime and integrate external sandbox providers. These capabilities do not establish a uniform automatically expanding complete RootFS. Verify system-path retention and online growth on the actual backend, without inferring that every connected provider lacks those features.

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.

See paused file operations →

Provider selection changes the execution contract

Current documentation distinguishes provider-owned environments and required credentials. Eval runs in the current process without isolation; Jupyter, Docker and hosted providers have different execution boundaries. Server-side notebook execution can continue after browser reconnection. These features do not establish one whole-RootFS, checkpoint or durability contract across all providers.

Source 1 ↗Source 2 ↗

Content attachment is not uniform across backends

Datalayer Runtime supports attaching and detaching its Home Folder while running. Other content types and the documented Daytona/E2B/Modal paths fix mounts at creation, so a changed attachment requires a new sandbox. An unsupported live attachment is rejected. Evaluate the exact mounted data and installed system paths instead of assuming a successful notebook reconnect preserves the entire machine.

Source 1 ↗

Reserved runtime and agent-plan allowances are separate

The credit guide reserves the requested runtime duration upfront and refunds unused time on early termination; idle running time consumes credits too. The current price page separately shows agent-run quotas, wallet allowances and organization seat billing. A monthly agent-run count is neither simultaneous-machine capacity nor an all-in external-provider compute allowance.

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.

Datalayer Runtimes

Pricing reviewed 2026-10-18

Free plan
$0
Three agents, 500 agent runs/month and 50 included credits reset each calendar month.
Rate source ↗
Team base plan
$49/month
5,000 agent runs/month and 500 wallet credits each billing cycle.
Rate source ↗
Team organization active seats
$15/active seat/month in addition to the base plan
Organization billing rule; do not assume the personal plan has the same seat meter.
Rate source ↗
Available managed CPU environment
$0.30/hour; 1 vCPU and 1 GiB RAM
The same table lists 3 credits/hour. Other displayed CPU/GPU shapes are marked unavailable.
Rate source ↗
Enterprise
Custom pricing and seat terms
Rate source ↗

The current price page says LLM token usage is tracked but not yet deducted from wallet credits, with charging planned later; confirm effective model/provider terms. Third-party execution providers can have their own bills and requirements. Runtime duration, plan run quotas and wallet top-ups are distinct meters. No unavailable GPU rate or directory-derived monthly scenario is presented as a current offer.

Check current Datalayer Runtimes 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 Datalayer Runtimes

  1. Record provider/environment selection, notebook and agent state, content attachments, external credentials, runtime reservations and the account’s billing entity.
  2. Build and validate the required execution-provider integration for Sandbox0 while retaining notebook, data, agent specification and governance behavior.
  3. Test system tools and arbitrary persistent paths, growing outputs, paused files, process expectations, mount changes and the combined plan/runtime/model/provider bill.

Common questions

Is Sandbox0 a drop-in Datalayer Runtimes 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 ↗datalayer.ai/docs/code-sandbox-providers ↗datalayer.ai/docs/code-sandboxes ↗datalayer.ai/docs/credits ↗datalayer.ai/pricing ↗Sandbox0 RootFS capacity →

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