DBMS > Amazon DocumentDB vs. Datastax Enterprise vs. Microsoft SQL Server vs. Prometheus vs. Warp 10

System Properties Comparison Amazon DocumentDB vs. Datastax Enterprise vs. Microsoft SQL Server vs. Prometheus vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Microsofts flagship relational DBMS

Open-source Time Series DBMS and monitoring system

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/documentdb

www.datastax.com/products/datastax-enterprise

www.microsoft.com/en-us/sql-server

prometheus.io

www.warp10.io

Technical documentation

aws.amazon.com/documentdb/resources

docs.datastax.com

learn.microsoft.com/en-US/sql/sql-server

prometheus.io/docs

www.warp10.io/content/02_Getting_started

Developer

DataStax

Microsoft

SenX

Initial release

2019

2011

1989

2015

Current release

6.8, April 2020

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

Apache License 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.

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Implementation language

Java

C++

Java

Server operating systems

hosted

Linux
OS X

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP/JSON API

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

configurable replication factor, datacenter aware, advanced replication for edge computing

yes, but depending on the SQL-Server Edition

yes

by Federation

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

Atomicity and isolation are supported for single operations

ACID

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

User concepts

Access control

Access rights for users and roles

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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