DBMS > Apache Druid vs. OrientDB vs. SwayDB vs. TigerGraph

System Properties Comparison Apache Druid vs. OrientDB vs. SwayDB vs. TigerGraph

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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

Multi-model DBMS (Document, Graph, Key/Value)

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store

Key-value store

Graph DBMS

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

Score	2.67
Rank	#107	Overall
	#53	Relational DBMS
	#7	Time Series DBMS

Score	5.33
Rank	#68	Overall
	#10	Document stores
	#3	Graph DBMS
	#10	Key-value stores

Score	0.07
Rank	#306	Overall
	#47	Key-value stores

Score	1.40
Rank	#147	Overall
	#12	Graph DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

www.orientdb.com/docs/last/index.html

docs.tigergraph.com

Developer

Apache Software Foundation and contributors

OrientDB LTD; CallidusCloud; SAP

Simer Plaha

Initial release

2012

2010

2018

2017

Current release

0.20.0, October 2020

3.1.0, June 2020

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache version 2

Open Source

GNU Affero GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

C++

Server operating systems

Linux
OS X
Unix

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

yes

schema-less columns are supported

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

yes

Typing

predefined data types such as float or date

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

SQL for querying

SQL-like query language, no joins

SQL-like query language (GSQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
Kotlin
Scala

C++
Java

Server-side scripts

Stored procedures

Java, Javascript

yes

Triggers

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Atomic execution of operations

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

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

Access rights for users and roles; record level security configurable

Role-based access control

More information provided by the system vendor

Specific characteristics

TigerGraph is a native graph database, with massively parallel processing and fully...
» more

Competitive advantages

TigerGraph is the fastest and most scalable graph platform, powered by a native parallel...
» more

Typical application scenarios

Anti Money Laundering Real-Time Fraud Detection Customer 360 Real-Time Personalized...
» more

Key customers

Four out of the top five global banks use TigerGraph for real-time fraud detection....
» more

Market metrics

ANALYST RESEARCH Nov 2020: TigerGraph Named A Leader For Graph Data Platforms - TigerGraph...
» more

Licensing and pricing models

Try TigerGraph for Free in the Cloud or On Prem https://www.tigergraph.com/get-tigergraph/...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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