DBMS > CockroachDB vs. Spark SQL vs. TempoIQ vs. Valentina Server

System Properties Comparison CockroachDB vs. Spark SQL vs. TempoIQ vs. Valentina Server

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

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.

Spark SQL is a component on top of 'Spark Core' for structured data processing

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Object-relational database and reports server

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.cockroachlabs.com

spark.apache.org/sql

tempoiq.com (offline)

www.valentina-db.net

Technical documentation

www.cockroachlabs.com/docs

spark.apache.org/docs/latest/sql-programming-guide.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Cockroach Labs

Apache Software Foundation

TempoIQ

Paradigma Software

Initial release

2015

2014

2012

1999

Current release

23.1.1, May 2023

3.5.0 ( 2.13), September 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

Apache 2.0

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

Scala

Server operating systems

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

dynamic schema

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

JDBC
ODBC

HTTP API

ODBC

Supported programming languages

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

Java
Python
R
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Realtime Alerts

yes

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

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

yes

User concepts

Access control

Role-based access control

simple authentication-based access control

fine grained access rights according to SQL-standard

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More resources

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