DBMS > AgensGraph vs. Drizzle vs. Google BigQuery vs. IRONdb vs. Memgraph

System Properties Comparison AgensGraph vs. Drizzle vs. Google BigQuery vs. IRONdb vs. Memgraph

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.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Large scale data warehouse service with append-only tables

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Time Series DBMS

Graph DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Website

bitnine.net/agensgraph

cloud.google.com/bigquery

www.circonus.com/solutions/time-series-database/

memgraph.com

Technical documentation

bitnine.net/documentation

cloud.google.com/bigquery/docs

docs.circonus.com/irondb/category/getting-started

memgraph.com/docs

Social network pages

Developer

Bitnine Global Inc.

Drizzle project, originally started by Brian Aker

Google

Circonus LLC.

Memgraph Ltd

Initial release

2016

2008

2010

2017

Current release

2.1, December 2018

7.2.4, September 2012

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GNU GPL

commercial

Free license available

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++

C and C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

hosted

Linux

Data scheme

depending on used data model

yes

schema-free

schema-free and schema-optional

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

yes

with proprietary extensions

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

Cypher Query Language
JDBC

JDBC

RESTful HTTP/JSON API

HTTP API

Bolt protocol
Cypher query language

Supported programming languages

C
Java
JavaScript
Python

C
C++
Java
PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes, in Lua

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Automatic, metric affinity per node

Sharding

dynamic graph partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users, roles and permissions

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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