SQL vs NoSQL

SQL vs NoSQL

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Most application developers have used SQL and possibly some NoSQL databases to build applications. YugabyteDB brings the best of these two databases together into one unified platform to simplify development of scalable cloud services.

Very often, today’s cloud services and applications will start out with just a few requests and a very small amount of data. These can be served by just a few nodes. But if the application becomes popular, they would have to scale out rapidly in order to handle millions of requests and many terabytes of data. YugabyteDB is well suited for these kinds of workloads.

Unifying SQL and NoSQL

Here are a few different criteria where YugabyteDB brings the best of SQL and NoSQL together into a single database platform.

Data characteristics

These can be loosely defined as the high-level concerns when choosing a database to build an application or a cloud service - such as its data model, the API it supports, its consistency semantics and so on. Here is a table that contrasts what YugabyteDB offers with SQL and NoSQL databases in general. Note that there are a number of different NoSQL databases each with their own nuanced behavior, and the table below is not accurate for all NoSQL databases - it is just meant to give an idea.

Database Characteristics	SQL	NoSQL	YugabyteDB
Data model	Well-defined schema (tables, rows, columns)	Schemaless	Both
API	SQL	Various	Goal - PostgreSQL + Cassandra + Redis
Consistency	Strong consistency	Eventual consistency	Strong consistency
Transactions	ACID transactions	No transactions	ACID transactions
High Write Throughput	No	Sometimes	Yes
Tunable read latency	No	Yes	Yes

Operational characteristics

Operational characteristics can be defined as the runtime concerns that arise when a database is deployed, run and managed in production. When running a database in production in a cloud-like architecture, there are a number of operational characteristics that become essential. Operationally here are the capabilities of YugabyteDB compared to SQL and NoSQL databases. As before, there are a number of NoSQL databases which are different in their own ways and the table below is meant to give a broad idea.

Operational Characteristics	SQL	NoSQL	YugabyteDB
Automatic sharding	No	Sometimes	Yes
Linear scalability	No	Yes	Yes
Fault tolerance	No - manual setup	Yes - smart client detects failed nodes	Yes - smart client detects failed nodes
Data resilience	No	Yes - but rebuilds cause high latencies	Yes - automatic, efficient data rebuilds
Geo-distributed	No - manual setup	Sometimes	Yes
Low latency reads	No	Yes	Yes
Predictable p99 read latency	Yes	No	Yes
High data density	No	Sometimes - latencies suffer when densities increase	Yes - predictable latencies at high data densities
Tunable reads with timeline consistency	No - manual setup	Sometimes	Yes
Read replica support	No - manual setup	No - no async replication	Yes - sync and async replication options

Core features

Applications and cloud services depend on databases for a variety of built-in features. These can include the ability to perform multi-row transactions, JSON or document support, secondary indexes, automatic data expiry with TTLs, and so on.

Here is a table that lists some of the important features that YugabyteDB supports, and which of YugabyteDB’s APIs to use in order to achieve these features. Note that typically, multiple databases are deployed in order to achieve these features.

Database Features	YugabyteDB - Cassandra-compatible YCQL API	YugabyteDB - Redis-compatible YEDIS API
Multi-row transactions	Yes	-
Consistent secondary indexes	Coming soon	-
JSON/document support	Roadmap - JSON datatype coming soon	Yes - supports primitive types, maps, lists, (sorted) sets
Secondary Indexes	Coming soon	-
High Throughput	Yes - batch inserts	Yes - pipelined operations
Automatic data expiry with TTL	Yes - table and column level TTL	Yes - key level TTL
Run Apache Spark for AI/ML	Yes	-

Linear scalability

In order to test the linear scalability of YugabyteDB, we have run some large cluster benchmarks (upto 50 nodes). We were able to scale YugabyteDB to million of reads and writes per second while retaining low latencies. You can read more about our large cluster tests and how we scaled YugabyteDB to millions of IOPS.

High performance

YugabyteDB was built with a performance as a design goal. Performance in a public cloud environment without sacrificing consistency is a serious ask. YugabyteDB has been written ground up in C++ for this very reason. Here is a chart showing how YugabyteDB compares with Apache Cassandra when running a YCSB benchmark. Read more about the YCSB benchmark results and what makes YugabyteDB performant.

The first chart below shows the total ops/second when running YBSB benchmark.

The second chart below shows the latency for the YCSB run.

Geo-distributed

This is a screenshot of YugabyteDB EE, which visualized the universe created. Below is a screenshot of a 5-node YugabyteDB universe created for a user identity use-case to power users logging in and changing passwords for a SaaS application. The replication factor of this universe is 5, and it is configured to keep 2 copies of data in us-west, 2 copies of the data in us-east and 1 copy of the data in asia-pacific region.

Because of this configuration, this universe can:

Allow low read latencies from any region (follower reads from a nearby datacenter)
Allow strongly consistent, global writes
Survive the outage of any region

The graphs above, also taken from the EE, show that the average read latencies for apps running the the various cloud regions are just 250 microseconds, while writes are strongly consistent and incur 218 milliseconds.

Multi-cloud ready

It is possible to easily configure YugabyteDB EE to work with multiple public clouds as well as private datacenters in just a few minutes.

1. SQL vs NoSQL