DBMS > HugeGraph vs. IRONdb vs. Microsoft Azure Synapse Analytics

System Properties Comparison HugeGraph vs. IRONdb vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

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

Description

A fast-speed and highly-scalable Graph DBMS

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Graph DBMS

Time Series DBMS

Relational DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

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

azure.microsoft.com/services/synapse-analytics

Technical documentation

hugegraph.apache.org/docs

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

docs.microsoft.com/azure/synapse-analytics

Developer

Baidu

Circonus LLC.

Microsoft

Initial release

2018

2017

2016

Current release

0.9

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

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++

Server operating systems

Linux
macOS
Unix

Linux

hosted

Data scheme

yes

schema-free

yes

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

also supports composite index and range index

yes

SQL

Support of SQL

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

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Groovy
Java
Python

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

C#
Java
PHP

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes, in Lua

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Automatic, metric affinity per node

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Users, roles and permissions

yes

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