DBMS > BigObject vs. CockroachDB vs. Prometheus vs. STSdb

System Properties Comparison BigObject vs. CockroachDB vs. Prometheus vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Open-source Time Series DBMS and monitoring system

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

Time Series DBMS

Key-value store

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

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

Website

bigobject.io

www.cockroachlabs.com

prometheus.io

github.com/STSSoft/STSdb4

Technical documentation

docs.bigobject.io

www.cockroachlabs.com/docs

prometheus.io/docs

Developer

BigObject, Inc.

Cockroach Labs

STS Soft SC

Initial release

2015

2011

Current release

23.1.1, May 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0, commercial license available

Open Source

Apache 2.0

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

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
macOS
Windows

Linux
Windows

Windows

Data scheme

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes, wire compatible with PostgreSQL

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC

RESTful HTTP/JSON API

.NET Client API

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using RAFT

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

none

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

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

Role-based access control

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More resources

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