DBMS > atoti vs. Drizzle vs. Microsoft Azure Synapse Analytics vs. SurrealDB

System Properties Comparison atoti vs. Drizzle vs. Microsoft Azure Synapse Analytics vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Object oriented DBMS

Relational DBMS

Document store
Graph DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Website

atoti.io

azure.microsoft.com/services/synapse-analytics

surrealdb.com

Technical documentation

docs.atoti.io

docs.microsoft.com/azure/synapse-analytics

surrealdb.com/docs

Developer

ActiveViam

Drizzle project, originally started by Brian Aker

Microsoft

SurrealDB Ltd

Initial release

2008

2016

2022

Current release

7.2.4, September 2012

v1.1.1, January 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

GNU GPL

commercial

Open Source

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

C++

Rust

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

C
C++
Java
PHP

C#
Java
PHP

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

Python

Transact SQL

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

yes, based on authentication and database rules

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More resources

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