DBMS > Microsoft Azure Cosmos DB vs. Oracle Coherence vs. QuestDB vs. Spark SQL vs. STSdb

System Properties Comparison Microsoft Azure Cosmos DB vs. Oracle Coherence vs. QuestDB vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Oracles in-memory data grid solution

A high performance open source SQL database for time series data

Spark SQL is a component on top of 'Spark Core' for structured data processing

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Score	2.48
Rank	#115	Overall
	#9	Time Series DBMS

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

azure.microsoft.com/services/cosmos-db

www.oracle.com/java/coherence

questdb.io

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/middleware/standalone/coherence

questdb.io/docs

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Microsoft

Oracle

QuestDB Technology Inc

Apache Software Foundation

STS Soft SC

Initial release

2014

2007

2014

2011

Current release

14.1, August 2023

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java (Zero-GC), C++, Rust

Scala

Server operating systems

hosted

All OS with a Java VM

Linux
macOS
Windows

Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

primitive types and user defined types (classes)

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

SQL with time-series extensions

SQL-like DML and DDL statements

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JCache
JPA
RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

JDBC
ODBC

.NET Client API

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C++
Java

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning (by timestamps)

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, with selectable consistency level

Source-replica replication with eventual consistency

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Multi-item ACID transactions with snapshot isolation within a partition

configurable

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

through memory mapped files

User concepts

Access control

Access rights can be defined down to the item level

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

News

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

Create an ADS-B flight radar with QuestDB and a Raspberry Pi
8 April 2024

Build a temperature IoT sensor with Raspberry Pi Pico & QuestDB
5 April 2024

Create an IoT server with QuestDB and a Raspberry Pi
4 April 2024

TimescaleDB vs. QuestDB: Performance benchmarks and overview
27 March 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.