DBMS > EJDB vs. EsgynDB vs. Google BigQuery vs. Heroic vs. Tibero

System Properties Comparison EJDB vs. EsgynDB vs. Google BigQuery vs. Heroic vs. Tibero

Editorial information provided by DB-Engines

Name

Description

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

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

Large scale data warehouse service with append-only tables

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A secure RDBMS, designed for easy portability from Oracle

Primary database model

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

github.com/Softmotions/ejdb

www.esgyn.cn

cloud.google.com/bigquery

github.com/spotify/heroic

us.tmaxsoft.com/products/tibero

Technical documentation

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

cloud.google.com/bigquery/docs

spotify.github.io/heroic

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Softmotions

Esgyn

Google

Spotify

TmaxSoft

Initial release

2012

2015

2010

2014

2003

Current release

6, April 2015

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache 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

C++, Java

Java

C and Assembler

Server operating systems

server-less

Linux

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

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.

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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