From 33da298f9a4e064699cfc037bcb01945a2eb27e9 Mon Sep 17 00:00:00 2001 From: Rishabh Bohra Date: Sat, 22 Aug 2020 06:15:02 +0530 Subject: [PATCH 1/2] Fix spelling typos --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 50dba40b..98d7d025 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,10 @@ -EinsteinDB is an embedded knwoledge base on relativistic sidecars: multi-consumer, multi-producer; console agnostic HTAP. +EinsteinDB is an embedded knowledge base on relativistic sidecars: multi-consumer, multi-producer; console agnostic HTAP. EinsteinDB as presented herein is a community edition DB-a-a-S built with Rust, Haskell, Docker, Kubernetes, Ansible and ❤️ -Along with MilevaDB, both components make up a cost-optimized distributed-SQL cluster with prolog querying, proto-buff generating, and regular -expression querying of Cold, Warm, and Hot Data Chunks. EinsteinDB implements a two-pronged Append-Merge Pull mechanism (similar to git). Because of EinsteinDB's Homomorphic Keyspace, MilevaDB can transmute key-value pairs as lock-free version-sharing secondary indices but for dirty pages pointing to trees. We define an einstein_merkle tree as the BtreeMapEngine invariant (or the HashMap) for B+Trees but guaranteeing better read-heavy throughpu. +Along with MilevaDB, both components make up a cost-optimized distributed-SQL cluster with prolog querying, protobuf generating, and regular +expression querying of Cold, Warm, and Hot Data Chunks. EinsteinDB implements a two-pronged Append-Merge Pull mechanism (similar to git). Because of EinsteinDB's Homomorphic Keyspace, MilevaDB can transmute key-value pairs as lock-free version-sharing secondary indices but for dirty pages pointing to trees. We define an einstein_merkle tree as the BtreeMapEngine invariant (or the HashMap) for B+Trees but guaranteeing better read-heavy throughput. -EinsteinDB and MilevaDB interact with SQLite(at the top layer), PostgresQL for persistence(middle layer), and LMDB's Iterator implementation (bottom layer). Designed for Write-Optimized Copy-on-Write Semantics, Repeatable Read isolation guarantees for HTAP, column cracking, and vectorized SIMD for OLAP/OLTP SparkQL streams. VioletaBFT is EinsteinDB's distributed consensus protocol implemented with Haskell. +EinsteinDB and MilevaDB interact with SQLite(at the top layer), PostgreSQL for persistence(middle layer), and LMDB's Iterator implementation (bottom layer). Designed for Write-Optimized Copy-on-Write Semantics, Repeatable Read isolation guarantees for HTAP, column cracking, and vectorized SIMD for OLAP/OLTP SparkQL streams. VioletaBFT is EinsteinDB's distributed consensus protocol implemented with Haskell. VioletaBFT is a Byzantine Fault Tolerant HoneyBadger/Raft protocol which provides consistency guarantees and maintains consensus between replicas. Unlike most of the competitors, VioletaBFT compiles to Rust (From Haskell) and pipelines a JIT Automatic failover with Partition persistence. 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