Distributed SQL
This article will address the topic of Distributed SQL, which has generated great interest due to its relevance today. Distributed SQL is a topic that has aroused the interest of many people in different areas, whether in the personal, academic, professional or social sphere. Over the years, Distributed SQL has gained greater importance and relevance, generating debates, research and reflections on its impact and consequences in our society. In this sense, it is essential to analyze and understand the different aspects surrounding Distributed SQL, from its origins to its evolution today, in order to offer a broad and complete vision of this very relevant topic.
A distributed SQL database is a single relational database which replicates data across multiple servers. Distributed SQL databases are strongly consistent and most support consistency across racks, data centers, and wide area networks including cloud availability zones and cloud geographic zones. Distributed SQL databases typically use the Paxos or Raft algorithms to achieve consensus across multiple nodes.
Sometimes distributed SQL databases are referred to as NewSQL but NewSQL is a more inclusive term that includes databases that are not distributed databases.
History
Google's Spanner popularized the modern distributed SQL database concept. Google described the database and its architecture in a 2012 whitepaper called "Spanner: Google's Globally-Distributed Database." The paper described Spanner as having evolved from a Big Table-like key value store into a temporal multi-version database where data is stored in "schematized semi-relational tables."[1]
Spanner uses atomic clocks with the Paxos algorithm to accomplish consensus with regards to state distributed between servers. In 2010, and earlier implementation, ClustrixDB (now MariaDB Xpand) moved from a hardware appliance to a Paxos-based software database[2] and was later acquired by MariaDB[3] and added to a SaaS cloud offering called SkySQL.[4] In 2015, two Google engineers left the company to create Cockroach DB which achieves similar results using the Raft algorithm without atomic clocks or custom hardware.[5]
Spanner is primarily used for transactional and time-series use cases. However, Google furthered this research with a follow on paper about Google F1 which it describes as a Hybrid transactional/analytical processing database built on Spanner.[1]
Architecture
Distributed SQL databases have the following general characteristics:
- synchronous replication
- strong transactional consistency across at least availability zones (i.e. ACID compliance)[6]
- relational database front end structure – meaning data represented as tables with rows and columns similar to any other RDBMS
- automatically sharded data storage
- underlying key–value storage[7][1]
- native SQL implementation
Following the CAP Theorem, distributed SQL databases are "CP" or consistent and partition-tolerant. Algorithmically they sacrifice availability in that a failure of a primary node can make the database unavailable for writes.
All distributed SQL implementations require some kind of temporal synchronization to guarantee consistency. With the exception of Spanner, most do not use custom hardware to provide atomic clocks. Spanner is able to synchronize writes with temporal guarantees. Implementations without custom hardware require servers to compare clock offsets and potentially retry reads.[8]
Distributed SQL implementations
| Vendor | API | License model |
|---|---|---|
| Amazon Aurora | PostgreSQL & MySQL | Proprietary |
| CockroachDB | PostgreSQL-like | Proprietary |
| Google Spanner | Proprietary SQL-like | Proprietary |
| MySQL Cluster | MySQL | Open Source (GPLv2) |
| NuoDB | Proprietary SQL | Proprietary |
| YugabyteDB | PostgreSQL & Cassandra CQL-like | Open Source (Apache 2.0) |
| TiDB | MySQL-like | Open Source (Apache 2.0) |
| MariaDB XPand | MariaDB | Proprietary |
| Teradata | Proprietary SQL-like | Proprietary |
| YDB[9] | Proprietary SQL-like, PostgreSQL-like | Open Source (Apache 2.0) |
Compared to NewSQL
CockroachDB, YugabyteDB and others have at times referred to themselves as NewSQL databases. Some of the NewSQL databases have fundamentally different architectures, but were cited as examples of NewSQL by Matthew Aslett who coined the term.[10] In essence, distributed SQL databases are built from the ground-up and NewSQL databases include replication and sharding technologies added to existing client-server relational databases like PostgreSQL.[11] Some experts define DistributedSQL databases as a more specific subset of NewSQL databases.[12]
References
- ^ a b c https://storage.googleapis.com/pub-tools-public-publication-data/pdf/41344.pdf [bare URL PDF]
- ^ Higginbotham, Stacey (May 3, 2010). "Clustrix Builds the Webscale Holy Grail: A Database That Scales". gigaom.com.[dead link]
- ^ "MariaDB acquires Clustrix". 20 September 2018.
- ^ Baer (dbInsight), Tony. "For MariaDB, it's time to put the pieces together". ZDNet.
- ^ Morgan, Timothy Prickett (February 22, 2017). "Google Spanner Inspires CockroachDB To Outrun It". The Next Platform.
- ^ The future of databases: distributed SQL & MariaDB ®, retrieved 2022-12-21
- ^ "The Architecture of a Distributed SQL Database". 23 September 2020 – via www.youtube.com.
- ^ "Living Without Atomic Clocks". Cockroach Labs. April 21, 2020.
- ^ "YDB is an open-source Distributed SQL Database that combines high availability and scalability with strong consistency and ACID transactions". ydb.tech.
- ^ "What we talk about when we talk about NewSQL — Too much information".
- ^ "SQL vs. NoSQL Databases: What's the Difference?". www.ibm.com. 12 June 2022.
- ^ Prabagaren, Gokul (October 30, 2019). "NewSQL — The Next Evolution in Databases". Medium.