DBMS > BigObject vs. EDB Postgres vs. GridDB vs. SAP HANA vs. STSdb

System Properties Comparison BigObject vs. EDB Postgres vs. GridDB vs. SAP HANA vs. STSdb

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.

Scalable in-memory time series database optimized for IoT and Big Data

In-memory, column based data store. Available as appliance or cloud service

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

Secondary database models

Document store
Spatial DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

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

Website

bigobject.io

www.enterprisedb.com

griddb.net

www.sap.com/products/hana.html

github.com/STSSoft/STSdb4

Technical documentation

docs.bigobject.io

www.enterprisedb.com/docs

docs.griddb.net

help.sap.com/hana

Developer

BigObject, Inc.

EnterpriseDB

Toshiba Corporation

SAP

STS Soft SC

Initial release

2015

2005

2013

2010

2011

Current release

14, December 2021

5.1, August 2022

2.0 SPS07 (April 4, 2023), April 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

free community edition available

commercial

BSD for PostgreSQL-components

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

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

Linux

Appliance or cloud-service

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC

.NET Client API

Supported programming languages

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

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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.

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

by hash, list or range

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate 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

ACID at container level

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 can be defined per database

yes

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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.