DBMS > Ignite vs. Memgraph vs. Microsoft Azure Cosmos DB vs. Teradata

System Properties Comparison Ignite vs. Memgraph vs. Microsoft Azure Cosmos DB vs. Teradata

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

Globally distributed, horizontally scalable, multi-model database service

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Key-value store
Relational DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

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	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

ignite.apache.org

memgraph.com

azure.microsoft.com/services/cosmos-db

www.teradata.com

Technical documentation

apacheignite.readme.io/docs

memgraph.com/docs

learn.microsoft.com/azure/cosmos-db

docs.teradata.com

Social network pages

Developer

Apache Software Foundation

Memgraph Ltd

Microsoft

Teradata

Initial release

2015

2017

2014

1984

Current release

Apache Ignite 2.6

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache 2.0

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

C++, Java, .Net

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux

hosted

hosted
Linux

Data scheme

yes

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 properties auto-indexed by default

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

SQL 2016 + extensions

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Bolt protocol
Cypher query language

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

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.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++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

JavaScript

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes (cache interceptors and events)

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

Sharding

Implicit feature of the cloud service

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

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

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

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.

yes

User concepts

Access control

Security Hooks for custom implementations

Users, roles and permissions

Access rights can be defined down to the item level

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.