BLOCKY ZipperChain Ledger

• BLOCKY ZipperChain is a digital ledger architecture that bypasses traditional consensus by leveraging trusted cloud services to enforce transaction immutability and fast finality.
• It replaces peer-to-peer voting with a fixed pipeline of timestamp, sequencer, and replication services, ensuring global agreement via cryptographic attestations.
• Empirical data show finality latencies of around 427–805 ms and throughput reaching up to 1.5 million transactions per second in cloud-based environments.

BLOCKY ZipperChain is a digital ledger architecture that dispenses with classical distributed consensus mechanisms, replacing them with a sequential pipeline of specialized, highly durable cloud services. Designed for usage in environments where users already trust existing cloud-based services, it achieves transaction immutability, global agreement, and persistent availability by “transmuting” these trust assumptions onto the ledger itself. BLOCKY ZipperChain is characterized by extraordinarily low finality latency—on the order of hundreds of milliseconds—and throughput that approaches data center network line speeds, all without employing a native token or maintaining a large pool of incentivized verifiers (Bjornsson et al., 26 Nov 2025).

1. Architecture and Building Blocks

BLOCKY ZipperChain eschews the peer-to-peer, majority-vote models of Proof-of-Work (PoW), Proof-of-Stake (PoS), or classical BFT consensus. Instead, it interposes three cloud services in a fixed pipeline:

• Trusted Timestamp Service: Issues signed, real-world clock timestamps (e.g., via JWT, as with AWS Cognito or Auth0).
• Trusted Sequencer Service: Assigns strictly increasing sequence numbers to unique inputs. Implemented within secure enclaves (e.g., AWS Nitro Enclave).
• Trusted Replication Service: Provides high-durability, immutable storage through WORM-mode (Write Once, Read Many) cloud buckets combined with erasure coding (e.g., RLNC across six regions).

Transactions are submitted by users into a FIFO queue. A central process, “ZipIt,” executes periodic batching, construction of Merkle trees, block formation, timestamping, sequencing, and durable replication, all over a high-speed data-center network. There is no distributed consensus, leader election, or multi-party voting (Bjornsson et al., 26 Nov 2025).

2. Security and Trust Assumptions

The security model of BLOCKY ZipperChain leverages the already-assumed trust in the participating services:

• Trust in the Timestamp Service’s private key integrity and clock accuracy.
• Trust in the Sequencer Service’s Nitro Enclave isolation and attested public key.
• Trust in the Replication Service’s durable and immutable storage, underpinned by WORM semantics and RLNC sharding across geographically distributed data centers.

Formally, core artifacts called “triads” encode block data, timestamp attestations, and sequence attestations. Each triad

$A = (b, t, s)$

with $b$ (block), $t$ (timestamp attestation), and $s$ (sequence attestation), is considered a “true triad” if all cryptographic linkages and signatures validate:

• The timestamp attestation $t$ signs the block $b$ and is signed by $K_T$ (Timestamp Service key).
• The sequencer attestation $s$ signs the timestamp $t$ and is signed by $K_S$ (Sequencer Service key).

The partial order on triads is defined lexicographically by block height and sequence number, guaranteeing a single consistent chain (Bjornsson et al., 26 Nov 2025).

3. Block Construction Workflow

Operation proceeds via the following dataflow, orchestrated by the ZipIt process:

1. Write: User submits a transaction, enqueued in FIFO.
2. Batching and Merkleization: At periodic intervals, a batch is dequeued, and a Merkle tree is constructed over the batch.
3. Block Construction: A new block $b$ is generated, anchoring the previous timestamp.
4. Replication: The Merkle tree and block are replicated to the Replication Service.
5. Timestamping: The block’s hash is submitted to the Timestamp Service for signed timestamp attestation.
6. Replication (cont.): The block and its timestamp are replicated.
7. Sequencing: The timestamp’s hash is sent to the Sequencer Service, which assigns an incrementing counter and returns attestation.
8. Replication: The sequencer attestation is replicated.
9. State Update: Previous timestamp reference is advanced.

Consensus is thus replaced with sequential, attestable commitments by the three services—no majority, no miner incentives, no slashing. Each block’s chain of hash-linked triads serves both as the ordering mechanism and as the audit trail for accountability (Bjornsson et al., 26 Nov 2025).

4. Formal Properties: Immutability, Agreement, Availability

BLOCKY ZipperChain explicitly meets three foundational blockchain properties without distributed consensus:

• Immutability: Any tampering with a block or even a single Merkle leaf breaks the cryptographic hash-linking, producing mismatches with timestamp or sequencer signatures. Thus, once a transaction is observed as part of the chain by any honest participant, it will persist in that order for all subsequent users.
• Agreement: The partial order and deterministic successor selection (lowest sequence number, matching predecessor attestation) enforce a unique maximal chain of “true triads.” Forks are impossible to extend or inconsistently maintain, securing global linearizability.
• Availability: Probability of data loss or inaccessibility is negligible ($\Pr[\text{triad unavailable}] \leq 10^{-14}$ over 100 years), due to WORM and RLNC replication over multiple cloud regions.

These guarantees follow contingent on all three trusted services remaining uncompromised (Bjornsson et al., 26 Nov 2025).

5. Performance Characteristics

BLOCKY ZipperChain’s performance is determined by batching interval, Merkle tree construction, timestamp and sequencing latencies, network capacity, and object replication overhead. The finality latency for a single block is

$$t_{\rm finality} = \Delta_{\rm m} + \Delta_{\rm ts} + \Delta_{\rm bt} + \Delta_{\rm seq} + \Delta_{\rm rep}$$

where constituent terms denote Merkleization, timestamp round-trip, replication, sequencing round-trip, and replication of the sequencing attestation.

Measured values demonstrate $t_{\rm finality} \approx 427$ ms under idle conditions and up to $805$ ms in high-throughput settings. Throughput is constrained by either the batching interval or network bandwidth:

$$R_{\max} = \min\left(\frac{n}{\Delta_{\rm batch}}, \frac{B_{\rm net}}{S_{\rm tx}}\right)$$

Empirical deployment (10 Gbps link, compact transaction hashes) yields ~18,000 tx/s; theoretical limits exceed 1.5 million tx/s for 64-byte transactions (Bjornsson et al., 26 Nov 2025).

6. Comparison with Consensus-Based Distributed Ledgers

Comparison to classical blockchain paradigms highlights differentiators:

Model	Trust Assumption	Finality	Throughput	Tokenomics
PoW (Bitcoin)	$>50\%$ honest hash-power	~1 hour	~7 tx/s	Rewarded coin, fees
PoS/BFT	$>2/3$ honest stake/voters	2–30 s	100–2,000 tx/s	Stake, slashing, fees
PoA	Known authorities	$<$1 s	$10^4$ tx/s	Often none, service fees
ZipperChain	Honest timestamp, sequencer, storage	$\sim$0.5 s	$10^4$–$10^6$ tx/s	None

BLOCKY ZipperChain exhibits permissioned, sub-second finality, but stands apart in eliminating distributed consensus entirely, forgoing native tokens, staking, and slashing. The core tradeoff is reduced trust decentralization: correctness is predicated on the integrity of a handful of cloud-based services, particularly the Nitro Enclave-based sequencer and multi-region WORM storage (Bjornsson et al., 26 Nov 2025).

7. Implications, Applications, and Limitations

BLOCKY ZipperChain demonstrates that atomic broadcast of transaction data with strong ordering and durability can be achieved without distributed consensus, provided practical trust in well-audited, high-assurance services exists. Use cases are plausible in enterprise and cloud-native applications where such trust assumptions are operationally justified. The absence of mining, staking, or token-based incentives significantly simplifies economic and governance layers but limits applicability in fully permissionless settings.

A plausible implication is that similar architectures may be designed for high-throughput, low-latency ledgers in environments where cloud service integrity is deemed sufficient, potentially reshaping a subset of distributed database and ledger deployments toward pipeline-oriented, cloud-assured models (Bjornsson et al., 26 Nov 2025).