DBMS > Apache Impala vs. CockroachDB vs. Riak KV vs. SAP HANA vs. Sequoiadb

System Properties Comparison Apache Impala vs. CockroachDB vs. Riak KV vs. SAP HANA vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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.

Distributed, fault tolerant key-value store

In-memory, column based data store. Available as appliance or cloud service

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Key-value store

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

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

impala.apache.org

www.cockroachlabs.com

www.sap.com/products/hana.html

www.sequoiadb.com

Technical documentation

impala.apache.org/impala-docs.html

www.cockroachlabs.com/docs

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

help.sap.com/hana

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cockroach Labs

OpenSource, formerly Basho Technologies

SAP

Sequoiadb Ltd.

Initial release

2013

2015

2009

2010

2013

Current release

4.1.0, June 2022

24.1.0, May 2024

3.2.0, December 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0, commercial license available

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Erlang

C++

Server operating systems

Linux

Linux
macOS
Windows

Linux
OS X

Appliance or cloud-service

Linux

Data scheme

yes

dynamic schema

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes, wire compatible with PostgreSQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC

HTTP API
Native Erlang Interface

JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

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

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Erlang

SQLScript, R

JavaScript

Triggers

yes

pre-commit hooks and post-commit hooks

yes

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

Sharding

no "single point of failure"

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using RAFT

selectable replication factor

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

ACID

Document is locked during a transaction

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Role-based access control

yes, using Riak Security

yes

simple password-based access control

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