DBMS > CrateDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. Microsoft Azure Table Storage vs. ScyllaDB

System Properties Comparison CrateDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. Microsoft Azure Table Storage vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Globally distributed, horizontally scalable, multi-model database service

Database as a Service offering with high compatibility to Microsoft SQL Server

A Wide Column Store for rapid development using massive semi-structured datasets

Cassandra and DynamoDB compatible wide column store

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Wide column store

Secondary database models

Relational DBMS

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Key-value store

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

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Website

cratedb.com

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/products/azure-sql/database

azure.microsoft.com/en-us/services/storage/tables

www.scylladb.com

Technical documentation

cratedb.com/docs

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/en-us/azure/azure-sql

docs.scylladb.com

Developer

Crate

Microsoft

ScyllaDB

Initial release

2013

2014

2010

2012

2015

Current release

V12

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

commercial

Open Source

Open Source (AGPL), 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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

Java

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

cluster global secondary indices

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language

yes

SQL-like DML and DDL statements (CQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

RESTful HTTP API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

JavaScript

Transact SQL

yes, Lua

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

Implicit feature of the cloud service

yes, with always 3 replicas available

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

selectable replication factor

Representation of geographical distribution of servers is possible

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

Eventual Consistency
Read-after-write consistency on record level

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

Multi-item ACID transactions with snapshot isolation within a partition

ACID

optimistic locking

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

in-memory tables

User concepts

Access control

rights management via user accounts

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
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ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
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Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

See CrateDB pricing >
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ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.