DBMS > Microsoft Azure Cosmos DB vs. QuestDB vs. Sequoiadb vs. Solr vs. TinkerGraph

System Properties Comparison Microsoft Azure Cosmos DB vs. QuestDB vs. Sequoiadb vs. Solr vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

A high performance open source SQL database for time series data

NewSQL database with distributed OLTP and SQL

A widely used distributed, scalable search engine based on Apache Lucene

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Document store
Relational DBMS

Search engine

Graph DBMS

Secondary database models

Spatial DBMS

Relational DBMS

Spatial DBMS

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

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

azure.microsoft.com/services/cosmos-db

questdb.io

www.sequoiadb.com

solr.apache.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

learn.microsoft.com/azure/cosmos-db

questdb.io/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

solr.apache.org/resources.html

Developer

Microsoft

QuestDB Technology Inc

Sequoiadb Ltd.

Apache Software Foundation

Initial release

2014

2013

2006

2009

Current release

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2

Open Source

Apache 2.0

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 (Zero-GC), C++, Rust

C++

Java

Server operating systems

hosted

Linux
macOS
Windows

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

oid, date, timestamp, binary, regex

yes

supports customizable data types and automatic typing

yes

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

SQL with time-series extensions

SQL-like query language

Solr Parallel SQL Interface

APIs and other access methods

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

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

proprietary protocol using JSON

Java API
RESTful HTTP/JSON API

TinkerPop 3

Supported programming languages

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

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

over HTTP

.Net
C++
Java
PHP
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Groovy
Java

Server-side scripts

Stored procedures

JavaScript

Java plugins

Triggers

JavaScript

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning (by timestamps)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication with eventual consistency

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID for single-table writes

Document is locked during a transaction

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

through memory mapped files

yes

User concepts

Access control

Access rights can be defined down to the item level

simple password-based access control

yes

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

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