DBMS > Apache Impala vs. CouchDB vs. Datomic vs. RocksDB vs. Tibero

System Properties Comparison Apache Impala vs. CouchDB vs. Datomic vs. RocksDB vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

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Trend Chart

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	10.26
Rank	#45	Overall
	#7	Document stores

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Website

us.tmaxsoft.com/products/tibero

Technical documentation

impala.apache.org/impala-docs.html

docs.couchdb.org/en/stable

docs.datomic.com

github.com/facebook/rocksdb/wiki

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Cognitect

Facebook, Inc.

TmaxSoft

Initial release

2013

2005

2012

2013

2003

Current release

4.1.0, June 2022

3.3.3, December 2023

1.0.6735, June 2023

8.11.4, April 2024

6, April 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

limited edition free

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

Java, Clojure

C++

C and Assembler

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

RESTful HTTP API

C++ API
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Clojure
Java

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions in JavaScript

yes

Transaction Functions

Persistent Stored Procedure (PSM)

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

But extensive use of caching in the application peers

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

yes

Multi-source replication
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

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

planned for next version

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per database

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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