DBMS > Memgraph vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. TinkerGraph

System Properties Comparison Memgraph vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

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

Fully managed big data interactive analytics platform

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Spatial DBMS

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

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

memgraph.com

azure.microsoft.com/services/data-explorer

www.postgres-xl.org

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

Technical documentation

memgraph.com/docs

docs.microsoft.com/en-us/azure/data-explorer

www.postgres-xl.org/documentation

Social network pages

Developer

Memgraph Ltd

Microsoft

Initial release

2017

2019

2014

since 2012, originally named StormDB

2009

Current release

cloud service with continuous releases

10 R1, October 2018

License

Commercial or Open Source

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

Open Source

Mozilla public license

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

C and C++

Java

Server operating systems

Linux

hosted

Linux
macOS

Data scheme

schema-free and schema-optional

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-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

XML type, but no XML query functionality

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

distributed, parallel query execution

APIs and other access methods

Bolt protocol
Cypher query language

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

TinkerPop 3

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Groovy
Java

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

user defined functions

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

with snapshot isolation

ACID

MVCC

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

optional

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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