DBMS > Apache Doris vs. EsgynDB vs. Google Cloud Datastore vs. Oracle Coherence vs. Yaacomo

System Properties Comparison Apache Doris vs. EsgynDB vs. Google Cloud Datastore vs. Oracle Coherence vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Oracles in-memory data grid solution

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

doris.apache.org
github.com/apache/doris

www.esgyn.cn

cloud.google.com/datastore

www.oracle.com/java/coherence

yaacomo.com

Technical documentation

github.com/apache/doris/wiki

cloud.google.com/datastore/docs

docs.oracle.com/en/middleware/standalone/coherence

Developer

Apache Software Foundation, originally contributed from Baidu

Esgyn

Google

Oracle

Q2WEB GmbH

Initial release

2017

2015

2008

2007

2009

Current release

1.2.2, February 2023

14.1, August 2023

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++, Java

Java

Server operating systems

Linux

hosted

All OS with a Java VM

Android
Linux
Windows

Data scheme

yes

schema-free

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

SQL

Support of SQL

yes

SQL-like query language (GQL)

yes

APIs and other access methods

JDBC
MySQL client

ADO.NET
JDBC
ODBC

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

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

All languages supporting JDBC/ODBC/ADO.Net

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

using Google App Engine

Triggers

Callbacks using the Google Apps Engine

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

Multi-source replication using Paxos

yes, with selectable consistency level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

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
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

fine grained access rights according to SQL-standard

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

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
25 May 2024, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Using Arrow Flight SQL Protocol in Apache Doris 2.1 For Super Fast Data Transfer
8 May 2024, hackernoon.com

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20 December 2012, blogs.oracle.com

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