DBMS > Elasticsearch vs. SQLite vs. Teradata Aster vs. Tibero vs. YottaDB

System Properties Comparison Elasticsearch vs. SQLite vs. Teradata Aster vs. Tibero vs. YottaDB

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 distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Widely used embeddable, in-process RDBMS

Platform for big data analytics on multistructured data sources and types

A secure RDBMS, designed for easy portability from Oracle

A fast and solid embedded Key-value store

Primary database model

Search engine

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Relational DBMS

using the Octo plugin

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.elastic.co/elasticsearch

www.sqlite.org

us.tmaxsoft.com/products/tibero

yottadb.com

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.sqlite.org/docs.html

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

yottadb.com/resources/documentation

Developer

Elastic

Dwayne Richard Hipp

Teradata

TmaxSoft

YottaDB, LLC

Initial release

2010

2000

2005

2003

2001

Current release

8.6, January 2023

3.46.0 (23 May 2024), May 2024

6, April 2015

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Public Domain

commercial

Open Source

AGPL 3.0

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 and Assembler

Server operating systems

All OS with a Java VM

server-less

Linux

AIX
HP-UX
Linux
Solaris
Windows

Docker
Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

dynamic column types

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

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

yes

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

yes

by using the Octo plugin

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
OLE DB

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

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
Python
R

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

R packages

Persistent Stored Procedure (PSM)

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

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

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

Memcached and Redis integration

yes

planned for next version

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Users and groups based on OS-security mechanisms

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.