DBMS > BigObject vs. EDB Postgres vs. Hive vs. STSdb

System Properties Comparison BigObject vs. EDB Postgres vs. Hive vs. STSdb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

bigobject.io

www.enterprisedb.com

hive.apache.org

github.com/STSSoft/STSdb4

Technical documentation

docs.bigobject.io

www.enterprisedb.com/docs

cwiki.apache.org/confluence/display/Hive/Home

Developer

BigObject, Inc.

EnterpriseDB

Apache Software Foundation

initially developed by Facebook

STS Soft SC

Initial release

2015

2005

2012

2011

Current release

14, December 2021

3.1.3, April 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

free community edition available

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2

Open Source

GPLv2, commercial license available

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

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)

Linux
Windows

All OS with a Java VM

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard with numerous extensions

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Thrift

.NET Client API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

C++
Java
PHP
Python

C#
Java

Server-side scripts

Stored procedures

Lua

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

by hash, list or range

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

EDB unveils EDB Postgres AI
23 May 2024, InfoWorld

EDB Puts Postgres in the Middle of Analytics Workflow with New Lakehouse Stack
22 April 2024, Datanami

EDB Announces EDB Postgres® AI, an Intelligent Platform for Transactional, Analytical and AI Workloads
23 May 2024, GlobeNewswire

Nutanix partners with EDB to fit database service for AI – Blocks and Files
21 May 2024, Blocks & Files

EDB Postgres AI is a new platform for analytics workloads
23 May 2024, Techzine Europe

provided by Google News

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

GC Tuning for Improved Presto Reliability
11 January 2024, Uber

provided by Google News

Share this page