slap_slatedb provides Elixir bindings for SlateDB 0.17, an embedded key-value engine that keeps its data in object storage, such as S3. Your application opens a database and calls it directly; there is no database server to run. SlateDB batches writes to limit object-store requests. A database can also use a local directory or memory. The bindings use the Erlang VM's native implemented function (NIF) interface to call Rust code, built with Rustler.

Use slap_slatedb when you want direct control over keys, scans, transactions, and durability. It does not distribute databases across nodes or serve an HTTP API. To run many databases across several nodes, use slap_cluster. For a ready-made partitioned key-value store with conditional writes, use slap_kv.

About Slap

This package is part of Slap.

Slap provides Elixir bindings for SlateDB (an embedded key-value engine optimized for storing data in object storage), as well as services built on top of these bindings. The services run inside your application, on one node or several.

Services:

  • slap_streams: a Durable Streams server, with HTTP, long polling, and SSE
  • slap_kv: partitioned key-value storage with conditional writes, ordered scans, and an HTTP API
  • slap_files: file storage with metadata and conditional replacement; small files are kept in slap_kv records, which saves object-store PUTs
  • slap_yjs: Yjs documents for collaborative editing, with replication and presence across nodes

Building blocks:

  • slap_slatedb: the SlateDB bindings
  • slap_cluster: SlateDB databases run as shards across nodes, with placement, routing, and failover
  • slap_snapshot_log: an append-only log of changes that can be condensed into snapshots

Server distribution:

  • slap: all Slap server libraries and a standalone HTTP server for evaluating and benchmarking slap_streams and slap_kv

Inspection:

  • slap_inspect: a read-only TUI and CLI for browsing Slap data

The slap package pulls in all seven server libraries. If you only need a subset, add those packages directly.

Installation

Requires Elixir 1.18 or later and Erlang/OTP 25 or later.

To depend on slap_slatedb directly, add it to the dependencies in your application's mix.exs:

defp deps do
  [
    {:slap_slatedb, "~> 0.3.0"}
  ]
end

Run mix deps.get. API documentation is on HexDocs.

Prebuilt NIFs cover macOS and Linux, with glibc or musl, on arm64 and x86_64; rustler_precompiled downloads the one for your platform from GitHub during compilation and verifies its checksum. You don't need Rust.

On other platforms, or for builds without network access such as Nix sandbox builds, compile the NIF from source: install Rust 1.91 or later, add {:rustler, "~> 0.38"} to your dependencies, and either set SLAP_SLATEDB_BUILD=1 when you compile or add this to your app's config/config.exs:

config :rustler_precompiled, :force_build, slap_slatedb: true

Build from source in the same way when you depend on slap_slatedb by path or from git. Otherwise compilation uses the prebuilt NIF released for the version in slap_slatedb's mix.exs, which lacks native changes made after that release. Compilation and loading succeed, so the mismatch shows up only when the code runs.

Example

In an application that depends on slap_slatedb, run this in iex -S mix with a fresh local directory:

iex> {:ok, db} = Slap.SlateDB.open("my-db", store: {:local, "/tmp/slatedb"}); :ok
:ok

iex> {:ok, _seq} = Slap.SlateDB.put(db, "user:1", "ada", await_durable: true); :ok
:ok
iex> {:ok, "ada"} = Slap.SlateDB.get(db, "user:1")
{:ok, "ada"}
iex> :ok = Slap.SlateDB.close(db)
:ok

await_durable: true waits for the write to reach the store before replying. Without it, the returned sequence identifies a write that may still be in flight. See Durability and write ordering before acknowledging data to a caller.

Capabilities

  • Reads and writes: get/3, put/4, delete/3 and batched write/3; range and prefix scans; per-key time to live (TTL), enforced during compaction; and snapshots for stable reads.
  • Transactions: snapshot and serializable isolation, with conflict retries through transaction/3. Built-in merge operators and a prefix compaction filter are available.
  • Durability: write sequence numbers, durable_seq/1, and subscribe/3 for durability notifications.
  • Object storage: Slap.SlateDB.ObjectStore supports conditional puts, streaming uploads and lazy downloads. Slap.SlateDB.Admin manages checkpoints, clones, compaction and garbage collection.
  • Observability: stats/1, metrics/1 and Slap.SlateDB.Telemetry.

The module documentation describes options and return values for each API.

snapshot/1 gives a read-only view of an open database; it is not a persisted checkpoint. Use create_checkpoint/2 for a durable view that can be reopened, or Slap.SlateDB.Admin.clone/3 to create an independently writable database from a checkpoint or the latest state. SlateDB's range projection and union operations for rescaling are not exposed by this binding.

How it works

Use one writer handle per database. You can share that handle between Elixir processes. Opening another writer for the same stored database fences the previous writer: it loses permission to make further durable writes. On shared storage, use Slap.SlateDB.Reader for additional read-only handles, including in other VMs, without taking over the writer's ownership.

Writes first enter an in-memory buffer. SlateDB batches them into write-ahead log (WAL) objects in the store. The buffer is also flushed into immutable sorted string tables (SSTs), files containing key/value records ordered by key. Keys and values can be arbitrary binaries. With persistent storage, a durable write survives restarting the writer because it is already recorded in the WAL or tables.

Flushed tables enter level zero (L0). Compaction merges and rewrites SSTs into sorted runs, groups of tables with non-overlapping key ranges. A manifest is metadata that records which tables and WAL data make up a database state. Checkpoints retain a manifest and its referenced data so that state can be reopened later.

Garbage collection (GC) removes obsolete objects after the current state and retained checkpoints no longer need them. Compaction creates replacement tables; GC reclaims the old files.

Native calls

I/O NIFs copy their arguments, start asynchronous Rust work on a shared Tokio runtime, and send the result to the calling Elixir process. A panic becomes an :internal error reply. Opening a store and converting large batches run off the normal Erlang schedulers.

close/2 waits for calls already in flight. Calls made after the handle closes fail with a :closed error. Snapshots, transactions, and iterators hold the database open. If the final handle is dropped without close/2, the destructor closes it in the background and logs a warning.

Binaries of at least 64 KiB share SlateDB buffers with Elixir. This avoids a copy, but a small slice can keep a larger cached block alive; use :binary.copy/1 when retaining such a value.

A call with a timeout uses a helper process so late replies can be discarded. The database operation continues after the caller times out. See Durability and write ordering before using timeouts with writes.

Runtime threads

The Tokio runtime is shared by every SlateDB database in the VM. By default it uses one worker thread per CPU. Set config :slap_slatedb, runtime_threads: 4 in config/runtime.exs or earlier, or set SLAP_SLATEDB_RUNTIME_THREADS=4 before starting the VM. Application config takes precedence when it is not nil. System.put_env/2 in config/runtime.exs works too; a call in your application's start/2 is too late because dependencies start first. Invalid values fail startup. Restart the VM to change the count.

More threads can increase concurrency, memory use and CPU contention. They do not shorten object-store requests or WAL flush intervals. Start with the default and measure throughput and latency with your expected workload and store. For example, run mix run bench/scenarios.exs once with the default and again with SLAP_SLATEDB_RUNTIME_THREADS=4; each run starts a new VM.

Object stores

SlateDB uses conditional writes to fence stale writers, so an object store must support them. S3, Azure Blob Storage, and RustFS do. Check other stores, including Google Cloud Storage, with probe_store/2 before use; see the notes below.

The :store option of open/2 selects where the database lives:

# In memory; each open/2 call creates a separate store.
Slap.SlateDB.open("my-db", store: :memory)

# A local directory.
Slap.SlateDB.open("my-db", store: {:local, "/var/lib/slatedb"})

# Amazon S3, configured from AWS_REGION, AWS_ACCESS_KEY_ID and
# AWS_SECRET_ACCESS_KEY.
Slap.SlateDB.open("my-db", store: {:url, "s3://my-bucket/prefix"})

# An S3-compatible store.
Slap.SlateDB.open("my-db",
  store:
    {:url, "s3://my-bucket/prefix",
     aws_endpoint: "http://127.0.0.1:9000",
     aws_allow_http: true,
     aws_region: "us-east-1",
     aws_access_key_id: "rustfsadmin",
     aws_secret_access_key: "rustfsadmin"}
)

# Azure Blob Storage, configured from AZURE_STORAGE_ACCOUNT_NAME and
# AZURE_STORAGE_ACCOUNT_KEY.
Slap.SlateDB.open("my-db", store: {:url, "az://my-container/prefix"})

# Google Cloud Storage, with a service account key file. Without one, the
# store uses application default credentials. See the GCS fencing note below.
Slap.SlateDB.open("my-db",
  store:
    {:url, "gs://my-bucket/prefix",
     google_service_account: "/etc/slatedb/service-account.json"}
)

With {:local, directory}, object writes and completed uploads sync file contents before returning success. On Unix, object creation and deletion also sync directory entries, and opening a store syncs its directory and ancestors. Synchronization can increase write and open latency. Persistence requires a filesystem and storage device that honor sync requests. Other platforms do not sync directory entries.

This applies to database storage and Slap.SlateDB.ObjectStore. Database writes still return before durability by default; use await_durable: true, durable_seq/1, or flush/1 to wait for or confirm durability.

Local stores support conditional writes (:create and {:update, version}), which SlateDB's garbage collector and slap_cluster's ObjectLease strategy need. Conditional updates require a filesystem that records modification times to the microsecond; on other filesystems they return :unsupported.

Every write to a local store holds one exclusive lock on the store's root directory until the write is synced, so writes to different databases and objects under one root run one at a time. Reads do not take the lock. Adding shards under one root does not increase write throughput; see choosing the shard count; before running a script against a store an application is using, see running another cluster on the same store.

The lock works only if every writer takes it:

  • Every process that uses the data must open the same root directory. A symlink to the root is resolved to it. A root inside another root is not supported.
  • Before upgrading, stop processes running older Slap versions. They, other object_store clients and programs that write to the directory directly do not take the lock.
  • Do not delete the .slap-lock#0 file in the root. Its presence does not mean a lock is held. Its modification time keeps object versions from repeating.

On Linux and macOS, opening a local store inspects its filesystem. Recognized network filesystems, including NFS and SMB/CIFS, are rejected. Unknown or ambiguous types, including FUSE and layered mounts, produce a warning once per root per process. Test locking and syncing on such a filesystem before using it.

A write whose sync fails returns an error even if the new object is already visible. After a failed conditional update, read the object's current version before retrying.

{:url, url, options} builds a store for s3:// (Amazon S3 and compatible stores), az:// / abfs:// / azure:// (Azure Blob Storage) or gs:// (Google Cloud Storage) URLs:

  • Configuration comes from environment variables (AWS_*, AZURE_* or GOOGLE_*), then from options, which win. Elixir reads the environment with System.get_env/0 and passes it to the NIF, so System.put_env/2 changes are seen. The builders' own from_env() reads the OS environment, which does not see them.

  • Unknown option keys are errors. aws_regoin: "..." returns {:error, %Slap.SlateDB.Error{kind: :invalid}} instead of being ignored. Unknown environment variables are skipped, as from_env does.

  • Conditional puts are always on. SlateDB fences stale writers with conditional puts on its manifest. For S3, object_store already defaults to ETag conditional puts, and the binding also sets them explicitly. A conditional_put value other than "etag", from the environment or from options, is an error. Azure and GCS support conditional puts without configuration.

  • Tested against emulators: the :s3 tests check fencing against RustFS, which answers 412 Precondition Failed to a conflicting If-Match or If-None-Match PUT. The :azure test checks it against Azurite.

  • GCS fencing is unverified here. object_store sends the documented x-goog-if-generation-match precondition, but no test in this repository has exercised it against GCS.

  • Probe stores before use. probe_store/2 checks whether a store rejects conflicting conditional puts. A store that ignores preconditions silently fails to fence a second writer. Run the probe against GCS and S3-compatible stores other than RustFS:

    {:ok, _steps} =
      Slap.SlateDB.probe_store({:url, "gs://my-bucket/prefix"}, "probe/check")

Durability and write ordering

The put, delete, merge, increment, and write calls return {:ok, seq}. A write is durable once durable_seq/1 is at least its seq. A process can write with await_durable: false and confirm several writes from one {:slap_slatedb_durable, ref, tag, durable_seq} notification.

Each call waits for its reply, and SlateDB assigns the sequence number before the reply is sent. One process's writes are applied in the order it makes them, each with a higher seq. Concurrent writes from different processes have no defined order. Code that calls the NIF directly without waiting for replies bypasses this ordering guarantee.

A write that returns {:error, %{kind: :timeout}} is still running and may be applied after the process's next write. If your code depends on write order, leave :timeout at its default of :infinity. After any write error, stop using the handle, close it, reopen the database, and reload state from storage.

A fenced writer detects the fence when it next writes or flushes, or when it next polls the manifest (every manifest_poll_interval, 1 s by default). Subscribers then get {:slap_slatedb_closed, ref, tag, :fenced}, so an idle owner finds out that it lost ownership without writing.

Closing a fenced handle returns :ok if the handle had already detected the fence. If the fence is detected during the close, close/2 returns {:error, %{kind: :closed, reason: :fenced}}, because writes that were not yet durable are lost. Both are normal shutdown results for a writer that lost ownership.

Clones, checkpoints and garbage collection

A clone is a separate database that you can write to. It starts with the source's data and shares the source's SST files instead of copying them. Slap.SlateDB.Admin.clone/3 clones the source at a checkpoint you pass, or at its latest state. It copies the WAL data the clone needs into the clone's path. Source and clone must be in the same store, under the same URL prefix. :memory stores cannot be used, because each :memory open is a separate store.

If you pass a checkpoint, you can delete it once clone/3 returns. If you do not, SlateDB creates a temporary one. Either way, SlateDB adds checkpoints of its own to the source, with no expiry, so that garbage collection keeps the files the clone shares. Do not delete those checkpoints.

A clone can be cloned in turn, so a database can read SST files owned by any of its ancestors. Do not delete an ancestor database's files while a descendant exists. Compaction rewrites a clone's shared files into files the clone owns. Garbage collection removes SlateDB's checkpoint from the source once neither the clone's current state nor any checkpoint of the clone needs the source's files. A checkpoint of the clone can therefore keep the source's checkpoint after the clone's current state no longer needs it.

Checkpoints with finite lifetimes stop protecting data when they expire. Once GC removes an expired checkpoint, opening a new reader or clone with its ID returns a Slap.SlateDB.Error. Keep a checkpoint alive for as long as its readers need it.

Limits and caveats

  • SlateDB 0.17 enforces TTL during compaction, not on reads. An expired row may still be returned; get_key_value/3 includes its expire_ts for an exact cutoff.
  • Numeric merge operators require an eight-byte base value and the same :merge_operator on every process that opens the database. An invalid base can fail reads and compaction. A batch cannot merge the same key with different TTLs.
  • A compaction filter deletes keys only when compaction rewrites them. Slap.SlateDB.Admin.compact/2 submits work on sorted runs and returns before it completes; it does not directly compact L0 files.
  • A Slap.SlateDB.Reader sees durable writes after its next manifest poll (its own manifest_poll_interval, 10 s by default, unlike the writer's 1 s). Its default :managed mode maintains a checkpoint to protect its reads from GC. mode: :latest creates no checkpoint, so reads can fail if GC removes a file they still need.
  • seq_for_timestamp/3 and timestamp_for_seq/3 use sampled points in the manifest; they are approximate.
  • Database and snapshot handles can be shared across processes. Use a transaction or iterator from one process at a time.

Unsupported SlateDB APIs

Compared with SlateDB's official UniFFI bindings, this binding does not expose:

  • merge operators and compaction filters written in Elixir
  • filter policies, segments and prefix extractors
  • the WAL reader
  • submitting arbitrary compaction specs, reading compaction state, and delete_db

SlateDB calls custom merge operators, compaction filters and filter policies synchronously from its own threads during reads, flushes and compactions, where no Elixir process is waiting. A NIF cannot call an Elixir function, so it would have to send a message and block the Tokio thread until a reply arrives. This deadlocks if the replying process is itself waiting on the database. The binding provides built-in operators and a prefix filter that you configure from Elixir. Logs and metrics can be sent to Elixir without waiting for a reply.

Build and test

Follow the repository's development setup, then run the commands in this section from slap_slatedb/.

export SLAP_SLATEDB_BUILD=1
mix test
mix test --include slow --include crash

The :slow test checks that slow I/O does not block schedulers. The crash test also runs against S3 when SLAP_TEST_S3_ENDPOINT is set.

SlateDB's own log records are off during tests. Set SLAP_TEST_LOG_LEVEL=warning (or debug, info, error) to see them.

The :s3 tests run against a real S3-compatible server when SLAP_TEST_S3_ENDPOINT is set. They check S3 configuration from the environment, durable writes, fencing through conditional puts, and clone and checkpoint retention through garbage collection. With RustFS in Docker:

docker run -d --name rustfs -p 9000:9000 \
  -e RUSTFS_ACCESS_KEY=rustfsadmin -e RUSTFS_SECRET_KEY=rustfsadmin rustfs/rustfs
curl --aws-sigv4 "aws:amz:us-east-1:s3" --user rustfsadmin:rustfsadmin \
  -X PUT http://127.0.0.1:9000/slatedb-test
SLAP_TEST_S3_ENDPOINT=http://127.0.0.1:9000 mix test

SLAP_TEST_S3_BUCKET, _REGION, _KEY and _SECRET override the defaults (slatedb-test, us-east-1, rustfsadmin, rustfsadmin).

The retention suite tests SlateDB 0.17.0 on local directories and RustFS. It covers checkpoint deletion and expiry, removal of the temporary checkpoint clone/3 creates, clones of clones, removal of SlateDB's checkpoints from sources, the WAL data copied into clones, and source writes before and after cloning. It compares full scans from fresh readers with caches disabled, checks that specific obsolete SSTs are deleted from each source database, and checks that a checkpoint of a clone keeps the source's checkpoint until it is deleted. GC runs with writers and readers closed. The suite does not cover removing ancestor storage, GC during writes, readers used after checkpoint expiry, other S3 implementations, or other SlateDB versions. Local cases run in ordinary checks; setting the S3 endpoint also enables the RustFS cases:

mix test test/clone_gc_test.exs
SLAP_TEST_S3_ENDPOINT=http://127.0.0.1:9000 mix test test/clone_gc_test.exs

The :stress cases require a durable source write to finish during the clone call. That completion depends on scheduling and I/O latency, so these cases are excluded from ordinary checks. Include the local stress case, or both stores with RustFS configured:

mix test test/clone_gc_test.exs --include stress:local
SLAP_TEST_S3_ENDPOINT=http://127.0.0.1:9000 mix test test/clone_gc_test.exs --include stress

The stress input on a manual run of the slap_slatedb workflow enables both local and RustFS stress cases in CI.

The fixtures close writers, compactors and readers before running GC with zero minimum object ages. They keep boundary files enabled and WAL fence collection disabled. These GC settings are for controlled tests.

The :azure test runs against Azurite when SLAP_TEST_AZURITE is set:

docker run -d --name azurite -p 10000:10000 mcr.microsoft.com/azure-storage/azurite \
  azurite-blob --blobHost 0.0.0.0 --skipApiVersionCheck --loose
python3 scripts/azurite_container.py slatedb
SLAP_TEST_AZURITE=1 mix test

There is no GCS integration test. object_store uses GCS's XML API, and each emulator tested (fake-gcs-server, storage-testbench, floci-gcp and localgcp, as of October 2026) lacks at least one required behavior: XML-API uploads, generation preconditions, or the ETag and x-goog-generation response headers. Tests cover GCS store configuration only.

Benchmarks

Run these scripts from slap_slatedb/ after the development setup above.

Run MIX_ENV=bench mix run bench/micro.exs to measure binding overhead on the in-memory store. mix run bench/scenarios.exs measures durable writes, reads, and scans against SLAP_BENCH_STORE=memory|local|s3; S3 uses SLAP_BENCH_S3_ENDPOINT. mix run bench/sweeps.exs measures latency and PUT rate across flush intervals and shard counts. The scripts write results under bench/results/.

A durable write waits for a WAL flush. Lowering flush_interval can reduce latency but increases object-store PUTs; each active database can issue up to one WAL PUT per interval. Measure against the store and machine you intend to use before choosing the interval and shard count.

License

Slap is released under the terms of the Apache License 2.0.

Copyright (c) 2026, Michael Russo.