DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. EJDB vs. Google Cloud Datastore vs. KairosDB vs. Sequoiadb

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. EJDB vs. Google Cloud Datastore vs. KairosDB vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Distributed Time Series DBMS based on Cassandra or H2

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store

Time Series DBMS

Document store
Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

github.com/Softmotions/ejdb

cloud.google.com/datastore

github.com/kairosdb/kairosdb

www.sequoiadb.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/datastore/docs

kairosdb.github.io

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Softmotions

Google

Sequoiadb Ltd.

Initial release

2016

2012

2008

2013

Current release

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

GPLv2

commercial

Open Source

Apache 2.0

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

hosted

server-less

hosted

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, details here

yes

oid, date, timestamp, binary, regex

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (GQL)

SQL-like query language

APIs and other access methods

JDBC
ODBC

in-process shared library

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

Graphite protocol
HTTP REST
Telnet API

proprietary protocol using JSON

Supported programming languages

C
Java
Perl
Python
R

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Java
JavaScript

Node.js
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

using Google App Engine

JavaScript

Triggers

yes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication using Paxos

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

fine grained access rights according to SQL-standard

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

simple password-based access control

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