# Centralized vs. Decentralized: Performance Comparison between BigchainDB and Amazon QLDB
## 4 Comparison between BigchainDB and QLDB
Other blockchain-based features include immutable data and transparency. Table 6 compares BigchainDB and QLDB based on various relevant criteria for the selection of the best database to use in developing an application. \begin{table}
\begin{tabular}{c c c} \hline
**Criteria** & **BigchainDB** & **QLDB** \\ \hline Website & [1] & [2] \\ \hline Initial release & 2016 & 10 September 2019 \\ \hline Current release & v.2.2.2, 29 September 2020 & 26 September 2022 \\ \hline \multirow{3}{*}{Use cases} & Intellectual property, identity, supply chain, government & Store financial transactions, reconcile supply chain systems, maintain claims history, centralize digital records \\ \hline Type & Public and private & Public and private \\ \hline Authentication and & Identity and access & Identity and access \\ authorization & management & management \\ \hline Pricing & Costly & Costly \\ \hline Blockchain type & Permissioned & Permissioned \\ \hline Immutability & Yes & Yes \\ \hline Decentralization & Yes & No \\ \hline Owner-controlled assets & Yes & Yes \\ \hline High transaction rate & Yes & Yes \\ \hline Low latency & Yes & Yes \\ \hline Indexing \& querying of & Yes \\ structured data & Yes & Yes \\ \hline Independent copies of the & Yes & No \\ ledger & & \\ \hline \multirow{3}{*}{Development facility} & Difficult, due to the node & Medium, based on a serverless architecture that provides automatic storage and resource scaling \\ \cline{1-1}  & configuration process & Medium, based on a serverless architecture that provides automatic storage and resource scaling \\ \cline{1-1}  & & \\ \end{tabular}
\end{table} 
Table 6: Comparison of BigchainDB and QLDB [7; 39; 40; 41]. Analysis was conducted in [42] in order to demonstrate the average writing response time for different centralized (MongoDB) and various decentralized solutions (HL-Sawtooth, HLF-Fabric, BigchainDB, HLGF-Burrow). In general, there is a significant difference between MongoDB (centralized) and the Blockchain platforms (decentralized). The writing latency indicates that the blockchain-based systems are slower, with BigchainDB being a middle-of-the-road performer. Regarding memory consumption and CPU utilization, usage is significantly higher for the distributed blockchain platforms that use the Proof of Stake (PoS) consensus mechanisms (such as HLGF-Burrow), however, this imposes higher resource consumption and time overheads compared to the other platforms. Both Hyperledger Fabric and BigchainDB use Raft (newer versions migrated to Kafka) [7] and Byzantine Fault Tolerant (BFT), respectively, and Hyperledger Sawtooth is configured to use Proof of Elapsed Time (PoET). It seems that PoS requires more compute power and memory consumption than Raft, BFT or PoET. As a general conclusion of this study, the PoET Blockchain, HL-Sawtooth solution was the most efficient in terms of average response time, CPU and memory consumption, tested in an IoT-based experiment. One limitation of the study is the lack of data from centralized & managed ledger databases such as QLDB or Google BigQuery [43].