DBMS > Apache Doris vs. Couchbase vs. IRONdb vs. Splice Machine vs. Trafodion

System Properties Comparison Apache Doris vs. Couchbase vs. IRONdb vs. Splice Machine vs. Trafodion

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

An MPP-based analytics DBMS embracing the MySQL protocol

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

www.couchbase.com

www.circonus.com/solutions/time-series-database/

splicemachine.com

trafodion.apache.org

Technical documentation

github.com/apache/doris/wiki

docs.couchbase.com

docs.circonus.com/irondb/category/getting-started

splicemachine.com/how-it-works

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation, originally contributed from Baidu

Couchbase, Inc.

Circonus LLC.

Splice Machine

Apache Software Foundation, originally developed by HP

Initial release

2017

2011

2017

2014

Current release

1.2.2, February 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

V0.10.20, January 2018

3.1, March 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C, C++, Go and Erlang

C and C++

Java

C++, Java

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

JDBC
MySQL client

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

HTTP API

JDBC
Native Spark Datasource
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes, in Lua

yes

Java

Java Stored Procedures

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Automatic Sharding

Automatic, metric affinity per node

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate consistency per node, eventual consistency across nodes

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

yes, multi-version concurrency control (MVCC)

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

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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