Sharding: a solution to the blockchain scalability problem

Sharding is one of the most promising approaches to increasing the throughput of distributed ledgers. The technology involves dividing the network into several independent subsystems (shards), each of which processes transactions in parallel. This allows for a significant increase in data processing speed and the number of operations per unit time without reducing the level of decentralization.

Mechanism of Action and Core Principles

From database theory to blockchain practice

The concept of splitting large storage systems into manageable fragments originates from traditional data management systems. In the context of distributed ledgers, this idea has been transformed into a technology that allows each network node to process not the entire amount of information, but only a specific part of it.

Sharding is a method in which the blockchain network is split into several concurrently functioning segments. Each segment contains a subset of data about balances and transactions, and its nodes operate independently of other segments. The result is a significant increase in overall performance without requiring all participants to store the entire information.

Sequential and parallel processing

Traditional architectures of distributed systems require each validating node to track and verify all operations. This guarantees security but creates a bottleneck: as the network grows, processing speed decreases. Nodes become increasingly overloaded, and hardware requirements grow exponentially.

Parallel processing addresses this problem fundamentally differently. Instead of each node processing all transactions sequentially, the load is distributed horizontally: data is divided into independent sets, and each segment works simultaneously with others. This creates a scalability effect: adding new nodes to one shard does not slow down the rest of the network.

Horizontal partitioning: why exactly this?

There are two approaches to database fragmentation. The horizontal approach divides information by rows — each fragment contains a complete set of fields for a specific subset of records. The vertical approach divides by columns — different nodes store different attributes of the same objects.

For blockchain networks, horizontal partitioning has proven to be the optimal solution for three reasons:

Scalability without compromises. Each shard functions as an independent system capable of processing operations simultaneously with others. This allows linear increase in network throughput.

Maintaining decentralization. Since a node does not need to store the entire blockchain history, hardware requirements are reduced. More participants can join the network as validators without access to expensive equipment.

Data integrity and verification. Each shard contains complete information about its transactions, allowing nodes to independently verify their segment’s data and maintain consensus without needing to synchronize with the entire network.

Benefits of Sharding for the Ecosystem

Accelerating operation processing

The main advantage is speed. When multiple shards process transactions simultaneously, overall capacity increases several times. Projects using this technology demonstrate impressive results: for example, Zilliqa achieves thousands of transactions per second through sharding. This opens the door for mass adoption by mainstream users.

Resource consumption optimization

In the traditional model, network growth means increased hardware requirements. Each new node must synchronize the entire history and store a full copy of the ledger. This inevitably leads to centralization: only organizations with powerful servers can participate in validation.

Sharding breaks this chain. Since each node only handles part of the data, memory and computing power requirements decrease significantly. This democratizes participation in the network and promotes true decentralization.

Increasing overall capacity

In traditional blockchains, adding new nodes often reduces performance: communication volume between participants increases, and synchronization becomes more complex. Sharding works oppositely: each new node joining a shard increases its local capacity without slowing down the rest of the network. Thus, the system scales subjectively: the more participants, the higher the performance.

Critical vulnerabilities and challenges

Attacks on individual shards

Reducing computational requirements for shard management creates a new danger. An attacker needs significantly fewer resources to seize one segment than to take over the entire network. Such attacks are called “1% attacks”: an aggressor can control a shard by controlling a small percentage of the network’s total power. A compromised shard can then generate fake transactions or block legitimate operations.

Cross-shard operation complexity

Operations between shards are a technical nightmare. If a user sends funds from one shard to another, the system must ensure that the transfer from the first shard occurs only after confirmation of receipt in the second. An error in this logic can lead to double spending: funds existing simultaneously in both shards. Solving this problem is difficult without significant delays in processing.

Availability and fault tolerance

If certain shards are temporarily offline (due to technical failures or DDoS attacks), the system will lose access to the data stored there. This can lead to loss of ledger integrity or inability to verify certain transactions. Maintaining the proper level of data redundancy requires substantial additional resources.

Load balancing and synchronization

Incorrect data distribution among shards can lead to their overload. Some shards may process significantly more transactions than others, creating bottlenecks. Additionally, synchronization between nodes under weak network conditions can slow down the entire process, especially if individual participants use equipment with limited computing power.

Ensuring network consensus

Without a reliable load distribution protocol, the system becomes unstable. There is a risk of asymmetric resource distribution, which can lead to loss of synchronization between shards and disruption of the entire chain’s integrity.

Implementation in Ethereum

The Ethereum platform is developing a comprehensive plan to implement sharding as part of the major Ethereum 2.0 upgrade. This is a multi-phase transition involving several critical stages.

In the final stages, Ethereum developers plan to fully implement a sharded architecture, where the network will consist of many concurrently functioning segments. This will allow Ethereum to significantly increase throughput and reduce transaction fees — two key issues of the current network state.

However, the path to this is not easy. Developers face fundamental challenges: how to ensure the security of each shard? How to guarantee proper communication between segments? How to avoid centralization when individual shards require fewer resources to manage?

The Ethereum team carefully tests each stage, conducting simulations of various attack and failure scenarios. Each component undergoes rigorous verification before integration into the mainnet.

Perspectives and concluding thoughts

Sharding is not just a technical trick but a fundamental approach to solving the so-called blockchain trilemma: simultaneously ensuring scalability, security, and decentralization. For a long time, these three properties seemed incompatible. Sharding has offered a new way.

The technology carries both enormous potential and real risks. On the one hand, it opens prospects for scaling blockchain without sacrificing its core values. On the other hand, it creates new classes of vulnerabilities requiring innovative solutions.

Various projects in the ecosystem see sharding as the likely future. For Ethereum, implementing this technology becomes a critical milestone on the way for the platform to compete with centralized systems in speed and cost while maintaining true decentralization and security.

Success will depend on ongoing research, experiments on testnets, and especially on the community of developers’ ability to anticipate and neutralize unforeseen problems. This is not a matter of the coming months but a long-term process of technological evolution.