DBMS > Blueflood vs. InfluxDB vs. Sequoiadb vs. SQLite vs. Teradata Aster

System Properties Comparison Blueflood vs. InfluxDB vs. Sequoiadb vs. SQLite 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

Scalable TimeSeries DBMS based on Cassandra

DBMS for storing time series, events and metrics

NewSQL database with distributed OLTP and SQL

Widely used embeddable, in-process RDBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

Time Series DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

blueflood.io

www.influxdata.com/products/influxdb-overview

www.sequoiadb.com

www.sqlite.org

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.influxdata.com/influxdb

www.sequoiadb.com/en/index.php?m=Files&a=index

www.sqlite.org/docs.html

Developer

Rackspace

Sequoiadb Ltd.

Dwayne Richard Hipp

Teradata

Initial release

2013

2000

2005

Current release

2.7.6, April 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

Server: AGPL; Client: Apache V2

Open Source

Public Domain

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++

Server operating systems

Linux
OS X

through Homebrew

Linux

server-less

Linux

Data scheme

predefined scheme

schema-free

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

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

oid, date, timestamp, binary, regex

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

yes

APIs and other access methods

HTTP REST

HTTP API
JSON over UDP

proprietary protocol using JSON

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

.Net
C++
Java
PHP
Python

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

Server-side scripts

Stored procedures

JavaScript

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

in enterprise version only

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

in enterprise version only

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

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Document is locked during a transaction

ACID

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.

yes

Depending on used storage engine

yes

User concepts

Access control

simple rights management via user accounts

simple password-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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