DBMS > HBase vs. Microsoft Access vs. RocksDB vs. Sphinx vs. Teradata Aster

System Properties Comparison HBase vs. Microsoft Access vs. RocksDB vs. Sphinx vs. Teradata Aster

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

Open source search engine for searching in data from different sources, e.g. relational databases

Platform for big data analytics on multistructured data sources and types

Primary database model

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

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

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

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

hbase.apache.org

www.microsoft.com/en-us/microsoft-365/access

rocksdb.org

sphinxsearch.com

Technical documentation

hbase.apache.org/book.html

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Facebook, Inc.

Sphinx Technologies Inc.

Teradata

Initial release

2008

1992

2013

2001

2005

Current release

2.3.4, January 2021

1902 (16.0.11328.20222), March 2019

8.11.4, April 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Bundled with Microsoft Office

Open Source

BSD

Open Source

GPL version 2, commercial licence available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Windows

Not a real database server, but making use of DLLs

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

schema-free, schema definition possible

yes

schema-free

yes

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

options to bring your own types, AVRO

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

full-text index on all search fields

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language (SphinxQL)

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

ADO.NET
DAO
ODBC
OLE DB

C++ API
Java API

Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

since Access 2010 using the ACE-engine

R packages

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

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

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

but no files for transaction logging

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

The original contents of fields are not stored in the Sphinx index.

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

a simple user-level security was built in till version Access 2003

fine grained access rights according to SQL-standard

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