DBMS > Apache Phoenix vs. Couchbase vs. InfinityDB vs. Teradata Aster

System Properties Comparison Apache Phoenix vs. Couchbase vs. InfinityDB vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

A Java embedded Key-Value Store which extends the Java Map interface

Platform for big data analytics on multistructured data sources and types

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	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Website

phoenix.apache.org

www.couchbase.com

boilerbay.com

Technical documentation

phoenix.apache.org

docs.couchbase.com

boilerbay.com/infinitydb/manual

Developer

Apache Software Foundation

Couchbase, Inc.

Boiler Bay Inc.

Teradata

Initial release

2014

2011

2002

2005

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

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

4.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

commercial

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

Java

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

All OS with a Java VM

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

in Aster File Store

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

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

yes

APIs and other access methods

JDBC

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

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

R packages

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

Ephemeral buckets

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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

fine grained access rights according to SQL-standard

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