DBMS > Apache Pinot vs. Axibase vs. CockroachDB vs. Microsoft Azure Cosmos DB

System Properties Comparison Apache Pinot vs. Axibase vs. CockroachDB vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

pinot.apache.org

axibase.com/docs/atsd/finance

www.cockroachlabs.com

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.pinot.apache.org

www.cockroachlabs.com/docs

learn.microsoft.com/azure/cosmos-db

Developer

Apache Software Foundation and contributors

Axibase Corporation

Cockroach Labs

Microsoft

Initial release

2015

2013

2015

2014

Current release

1.0.0, September 2023

15585

24.1.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0, commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java JDK11 or higher

Linux

Linux
macOS
Windows

hosted

Data scheme

yes

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

yes, wire compatible with PostgreSQL

SQL-like query language

APIs and other access methods

JDBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Go
Java
Python

Go
Java
PHP
Python
R
Ruby

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using RAFT

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Role-based access control

Access rights can be defined down to the item level

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