Open-Source Databases · zuoyebang

bitalostored

Bitalostored is a Redis-compatible distributed storage system that stores data on disk instead of memory, designed to reduce infrastructure costs while maintaining high performance. Built on the self-developed Bitalos engine, it scales horizontally to 1024 shards and supports multi-cloud disaster recovery.

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Source: GitHub — github.com/zuoyebang/bitalostored

2.2k

GitHub stars

154

Forks

Primary language

Apache-2.0

License (OSI-approved)

Key facts

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Field	Value
Repository	zuoyebang/bitalostored
Owner	zuoyebang
Primary language	Go
License	Apache-2.0 — OSI-approved
Stars	2.2k
Forks	154
Open issues	4
Latest release	v8.1.0 (2026-04-03)
Last updated	2026-04-03
Source	https://github.com/zuoyebang/bitalostored

What bitalostored is

Go-based distributed KV store with Redis protocol compatibility, featuring a custom B+-tree index (bitalostree), KV-separation (bithash), Raft-based replication with custom optimizations, and horizontal sharding. Architecture includes dashboard, proxy, and storage layers; supports transactions, Lua scripting, and multi-datacenter replication.

Quickstart

Get the bitalostored source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/zuoyebang/bitalostored.git2cd bitalostored3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Large-scale KV storage with cost optimization

Organizations managing 100GB–PB-scale datasets where memory-based caching (Redis) becomes prohibitively expensive. Disk-backed storage with 100μs read latency significantly reduces per-node cost compared to memory-only solutions.

Multi-region/multi-cloud deployments

Services requiring disaster recovery, geographic distribution, or compliance with data residency rules. Multi-datacenter replication and shard expansion in seconds enable fast failover and capacity adjustments without downtime.

High-throughput, low-latency transactional workloads

Scenarios demanding distributed ACID-like guarantees with Lua scripting and transaction support. The optimized Raft protocol and custom log engine (bitaloslog) support 30M QPS at 150μs write latency with 99.999% availability.

Implementation considerations

Cluster setup requires specifying shard count, replica count, and witness nodes upfront; shard expansion is fast but plan topology carefully to avoid re-sharding cycles.
Redis protocol compatibility covers most commands but may not include 100% of newer Redis 7+ features; validate command support against your workload before migration.
Operational expertise in distributed systems (Raft, sharding, failure recovery) is essential; the dashboard provides UI management, but troubleshooting complex scenarios requires deep architectural knowledge.
Storage overhead: disk I/O patterns differ from memory systems; monitor disk throughput and latency, especially during compaction and garbage collection of the KV-separation layer.
Data consistency model is eventual consistency in multi-master mode; strict ACID guarantees are limited to single-master deployments with Raft replication.

When to avoid it — and what to weigh

Sub-microsecond latency requirements — 100–150μs latency, while excellent for disk-based storage, may not meet ultra-low-latency trading or real-time control systems that demand in-memory responses.
Small datasets or memory-abundant environments — If your dataset fits comfortably in RAM and cost is not a constraint, in-memory solutions (Redis, Memcached) offer simpler operations and lower complexity.
Mature, audited third-party support required — Bitalostored is production-proven at Zuoyebang but lacks the vendor ecosystem and third-party support maturity of Redis. Enterprise support, SLA guarantees, and certified integrations are unknown.
Non-Docker/cloud-native mandatory deployments — Installation via shell scripts (install.sh/uninstall.sh) suggests on-premise or VM-based deployment. Native Kubernetes operators, Helm charts, or managed cloud services are not mentioned.

License & commercial use

Licensed under Apache License 2.0, a permissive OSI-approved license permitting commercial use, modification, and distribution with attribution and patent protections.

Apache-2.0 explicitly permits commercial use, proprietary modification, and closed-source redistribution of derived works. No license restrictions on commercial deployment. However, no explicit warranty, SLA, or commercial support model is documented; verify support arrangements separately with Zuoyebang.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	High
DEV.co fit	Good
Assessment confidence	High

Security considerations

No explicit security audit, penetration test results, or CVE history provided. Default credentials (demo/demo) used in quick-start must be changed for production. Network security (TLS, authentication) mechanisms not detailed; assume review of protocol implementation and deployment network isolation is necessary before handling sensitive data.

Alternatives to consider

Redis

Gold-standard in-memory KV store with massive ecosystem, vendor support, and lower operational overhead. Preferred if dataset fits in RAM and cost is secondary.

RocksDB/LevelDB-based systems (e.g., CockroachDB, TiKV)

Also disk-backed with better community documentation and audited security. CockroachDB adds SQL support and stronger ACID; TiKV offers Raft-based distribution but requires custom proxy/client logic.

Memcached or DragonflyDB

Simpler memory-based alternatives with lower operational complexity. DragonflyDB offers modern Redis compatibility with better performance; consider if memory cost is manageable.

Software development agency

Build on bitalostored with DEV.co software developers

Contact Devco to architect a proof-of-concept cluster, benchmark against your workload, and plan migration from Redis or other KV systems. We provide DevOps, cloud deployment, and custom backend expertise to accelerate adoption.

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bitalostored FAQ

Is Bitalostored a drop-in Redis replacement?

Mostly. It supports Redis protocol and most commands (SET, GET, LPUSH, SADD, ZADD, HSET, Lua, transactions). However, command coverage may not be 100%; test critical commands before production migration.

What is the typical latency compared to Redis?

Bitalostored: ~100μs read, ~150μs write (disk-backed). Redis in-memory: 1–10μs. The 10–150x difference is the tradeoff for disk storage cost savings and capacity scalability.

How many shards can Bitalostored handle?

Up to 1024 shards, enabling horizontal scaling across clusters. Shard expansion is fast (seconds) but requires cluster topology planning.

Is there commercial support or SLA?

Not documented. Zuoyebang uses it internally and open-source is stable, but no official SLA, support contracts, or managed service offering is mentioned; contact project authors for details.

Work with a software development agency

From first prototype to production, DEV.co delivers software development services around tools like bitalostored. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across open-source databases and beyond.

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