DBMS > CockroachDB vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. TimesTen

System Properties Comparison CockroachDB vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

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.

Fully managed big data interactive analytics platform

NewSQL database with distributed OLTP and SQL

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

column oriented

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.cockroachlabs.com

azure.microsoft.com/services/data-explorer

www.sequoiadb.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.cockroachlabs.com/docs

docs.microsoft.com/en-us/azure/data-explorer

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.oracle.com/database/timesten-18.1

Developer

Cockroach Labs

Microsoft

Sequoiadb Ltd.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2015

2019

2013

1998

Current release

24.1.0, May 2024

cloud service with continuous releases

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Server: AGPL; Client: Apache V2

commercial

Cloud-based only

Only available as a cloud service

yes

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
macOS
Windows

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

dynamic schema

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

yes

oid, date, timestamp, binary, regex

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

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

Kusto Query Language (KQL), SQL subset

SQL-like query language

yes

APIs and other access methods

JDBC

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

.Net
C++
Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

JavaScript

PL/SQL

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Azure Active Directory Authentication

simple password-based access control

fine grained access rights according to SQL-standard

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