DBMS > Apache Drill vs. CockroachDB vs. HarperDB vs. Riak KV vs. TempoIQ

System Properties Comparison Apache Drill vs. CockroachDB vs. HarperDB vs. Riak KV vs. TempoIQ

Editorial information provided by DB-Engines

Name

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

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Distributed, fault tolerant key-value store

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

drill.apache.org

www.cockroachlabs.com

www.harperdb.io

tempoiq.com (offline)

Technical documentation

drill.apache.org/docs

www.cockroachlabs.com/docs

docs.harperdb.io/docs

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Apache Software Foundation

Cockroach Labs

HarperDB

OpenSource, formerly Basho Technologies

TempoIQ

Initial release

2012

2015

2017

2009

2012

Current release

1.20.3, January 2023

23.1.1, May 2023

3.1, August 2021

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0, commercial license available

commercial

free community edition available

Open Source

Apache version 2, commercial enterprise edition

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

Node.js

Erlang

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

Linux
OS X

Data scheme

schema-free

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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

restricted

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes, wire compatible with PostgreSQL

SQL-like data manipulation statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HTTP API
Native Erlang Interface

HTTP API

Supported programming languages

C++

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Custom Functions

since release 3.1

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

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

A table resides as a whole on one (or more) nodes in a cluster

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes

the nodes on which a table resides can be defined

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

yes, using LMDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Role-based access control

Access rights for users and roles

yes, using Riak Security

simple authentication-based access control

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