DBMS > Amazon Redshift vs. BoltDB vs. Elasticsearch vs. ScyllaDB vs. Teradata Aster

System Properties Comparison Amazon Redshift vs. BoltDB vs. Elasticsearch vs. ScyllaDB 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

Large scale data warehouse service for use with business intelligence tools

An embedded key-value store for Go.

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

Cassandra and DynamoDB compatible wide column store

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Key-value store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

aws.amazon.com/redshift

github.com/boltdb/bolt

www.elastic.co/elasticsearch

www.scylladb.com

Technical documentation

docs.aws.amazon.com/redshift

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

docs.scylladb.com

Developer

Amazon (based on PostgreSQL)

Elastic

ScyllaDB

Teradata

Initial release

2012

2013

2010

2015

2005

Current release

8.6, January 2023

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Elastic License

Open Source

Open Source (AGPL), commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

Java

C++

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

Data scheme

yes

schema-free

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

schema-free

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

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

restricted

yes

All search fields are automatically indexed

yes

cluster global secondary indices

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

SQL-like DML and DDL statements (CQL)

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, Lua

R packages

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

selectable replication factor

Representation of geographical distribution of servers is possible

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

ES-Hadoop Connector

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

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

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

yes

Atomicity and isolation are supported for single operations

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

Memcached and Redis integration

yes

in-memory tables

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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