DBMS > Apache Druid vs. HugeGraph vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. TerminusDB

System Properties Comparison Apache Druid vs. HugeGraph vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

A fast-speed and highly-scalable Graph DBMS

Multi-storage database for search, including full-text search.

Globally distributed, horizontally scalable, multi-model database service

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS
Time Series DBMS

Graph DBMS

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

Document store
RDF store

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

druid.apache.org

github.com/hugegraph
hugegraph.apache.org

manticoresearch.com

azure.microsoft.com/services/cosmos-db

terminusdb.com

Technical documentation

druid.apache.org/docs/latest/design

hugegraph.apache.org/docs

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation and contributors

Baidu

Manticore Software

Microsoft

DataChemist Ltd.

Initial release

2012

2018

2017

2014

2018

Current release

29.0.1, April 2024

0.9

6.0, February 2023

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

Open Source

GPL version 2

commercial

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

Linux
OS X
Unix

Linux
macOS
Unix

FreeBSD
Linux
macOS
Windows

hosted

Linux

Data scheme

yes

schema-less columns are supported

yes

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

also supports composite index and range index

yes

full-text index on all search fields

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL for querying

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP API
TinkerPop Gremlin

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Groovy
Java
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

JavaScript
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

user defined functions

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

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

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Implicit feature of the cloud service

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

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

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users, roles and permissions

Access rights can be defined down to the item level

Role-based access control

More information provided by the system vendor

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.