DBMS > Memgraph vs. Microsoft SQL Server vs. Rockset vs. Sadas Engine vs. Solr

System Properties Comparison Memgraph vs. Microsoft SQL Server vs. Rockset vs. Sadas Engine vs. Solr

Editorial information provided by DB-Engines

Name

Description

An open source graph database built for real-time streaming and compatible with Neo4j

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

Spatial DBMS

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

Score	3.19
Rank	#94	Overall
	#8	Graph DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

memgraph.com

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

rockset.com

www.sadasengine.com

solr.apache.org

Technical documentation

memgraph.com/docs

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

docs.rockset.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

solr.apache.org/resources.html

Social network pages

Developer

Memgraph Ltd

Microsoft

Rockset

SADAS s.r.l.

Apache Software Foundation

Initial release

2017

1989

2019

2006

Current release

SQL Server 2022, November 2022

8.0

9.6.1, May 2024

License

Commercial or Open Source

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

restricted free version is available

commercial

free trial version available

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Java

Server operating systems

Linux

Linux
Windows

hosted

AIX
Linux
Windows

All OS with a Java VM

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

Data scheme

schema-free and schema-optional

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

dynamic typing

yes

supports customizable data types and automatic typing

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

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

Read-only SQL queries, including JOINs

yes

Solr Parallel SQL Interface

APIs and other access methods

Bolt protocol
Cypher query language

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

HTTP REST

JDBC
ODBC
Proprietary protocol

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

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

Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

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

Server-side scripts

Stored procedures

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

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

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

Automatic sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

with snapshot isolation

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

Access rights for users, groups and roles according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
» more

Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more

Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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