DBMS > BigObject vs. Databend vs. EJDB vs. Greenplum vs. Trafodion

System Properties Comparison BigObject vs. Databend vs. EJDB vs. Greenplum vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for real-time computations and queries

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Website

bigobject.io

github.com/datafuselabs/databend
www.databend.com

github.com/Softmotions/ejdb

greenplum.org

trafodion.apache.org

Technical documentation

docs.bigobject.io

docs.databend.com

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

docs.greenplum.org

trafodion.apache.org/documentation.html

Developer

BigObject, Inc.

Databend Labs

Softmotions

Pivotal Software Inc.

Apache Software Foundation, originally developed by HP

Initial release

2015

2021

2012

2005

2014

Current release

1.0.59, April 2023

7.0.0, September 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

Apache 2.0

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

Rust

C++, Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted
Linux
macOS

server-less

Linux

Data scheme

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

in-process shared library

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Lua

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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.

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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