DBMS > Elasticsearch vs. Memgraph vs. Microsoft Azure Cosmos DB vs. Tibero

System Properties Comparison Elasticsearch vs. Memgraph vs. Microsoft Azure Cosmos DB vs. Tibero

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Globally distributed, horizontally scalable, multi-model database service

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Search engine

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	3.19
Rank	#94	Overall
	#8	Graph DBMS

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

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

www.elastic.co/elasticsearch

memgraph.com

azure.microsoft.com/services/cosmos-db

us.tmaxsoft.com/products/tibero

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

memgraph.com/docs

learn.microsoft.com/azure/cosmos-db

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Social network pages

Developer

Elastic

Memgraph Ltd

Microsoft

TmaxSoft

Initial release

2010

2017

2014

2003

Current release

8.6, January 2023

6, April 2015

License

Commercial or Open Source

Open Source

Elastic License

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

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 and C++

C and Assembler

Server operating systems

All OS with a Java VM

Linux

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free and schema-optional

schema-free

yes

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 search fields are automatically indexed

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

Bolt protocol
Cypher query language

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

JavaScript

Persistent Stored Procedure (PSM)

Triggers

yes

by using the 'percolation' feature

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate 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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

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.

Memcached and Redis integration

yes

planned for next version

User concepts

Access control

Users, roles and permissions

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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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