DBMS > BigObject vs. etcd vs. Postgres-XL vs. SiteWhere

System Properties Comparison BigObject vs. etcd vs. Postgres-XL vs. SiteWhere

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

A distributed reliable key-value store

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Time Series 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	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

bigobject.io

etcd.io
github.com/etcd-io/etcd

www.postgres-xl.org

github.com/sitewhere/sitewhere

Technical documentation

docs.bigobject.io

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.postgres-xl.org/documentation

sitewhere1.sitewhere.io/index.html

Developer

BigObject, Inc.

SiteWhere

Initial release

2015

2014

since 2012, originally named StormDB

2010

Current release

3.4, August 2019

10 R1, October 2018

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

Open Source

Mozilla public license

Open Source

Common Public Attribution License Version 1.0

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

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)

FreeBSD
Linux
Windows

experimental

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

predefined scheme

Typing

predefined data types such as float or date

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

gRPC
JSON over HTTP

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

HTTP REST

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Users with fine-grained authorization concept

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

Recent citations in the news

ETCD guidelines: RBI seeks to balance rupee stability, competitiveness | Policy Circle
8 April 2024, Policy Circle

Public preview: AKS cluster control plane metrics in managed Prometheus
12 February 2024, Microsoft

Is Your etcd an Open Door for Cyber Attacks? How to Secure Your Kubernetes Clusters & Nodes
8 November 2023, Information Security Newspaper

Monitor Amazon EKS Control Plane metrics using AWS Open Source monitoring services
12 October 2023, AWS Blog

6 Cool Kubernetes Operators and How to Use Them
22 January 2024, hackernoon.com

provided by Google News

SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

Top Open-Source Tools for IoT Development in 2024
5 September 2024, Analytics Insight

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

Share this page