DBMS > Apache Druid vs. Google Cloud Datastore vs. OpenSearch vs. TigerGraph

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. OpenSearch 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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

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

Search engine

Graph DBMS

Secondary database models

Vector DBMS

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	4.47
Rank	#76	Overall
	#12	Document stores

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

druid.apache.org

cloud.google.com/datastore

github.com/opensearch-project
opensearch.org

www.tigergraph.com

Technical documentation

druid.apache.org/docs/latest/design

cloud.google.com/datastore/docs

opensearch.org/docs/latest

docs.tigergraph.com

Developer

Apache Software Foundation and contributors

Google

Amazon Web Services

Initial release

2012

2008

2021

2017

Current release

29.0.1, April 2024

2.5.0, January 2023

License

Commercial or Open Source

Open Source

Apache license v2

commercial

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.

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

hosted

All OS with a Java VM

Linux

Data scheme

yes

schema-less columns are supported

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

All search fields are automatically indexed

SQL

Support of SQL

SQL for querying

SQL-like query language (GQL)

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

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
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C++
Java

Server-side scripts

Stored procedures

using Google App Engine

yes

Triggers

Callbacks using the Google Apps Engine

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication using Paxos

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Relationships in graphs

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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.

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, groups and roles based on Google Cloud Identity and Access Management (IAM)

Role-based access control

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
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