DBMS > Firebolt vs. Hypertable vs. Kinetica vs. SQLite vs. TimesTen

System Properties Comparison Firebolt vs. Hypertable vs. Kinetica vs. SQLite vs. TimesTen

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

An open source BigTable implementation based on distributed file systems such as Hadoop

Fully vectorized database across both GPUs and CPUs

Widely used embeddable, in-process RDBMS

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	1.49
Rank	#148	Overall
	#68	Relational DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.firebolt.io

www.kinetica.com

www.sqlite.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.firebolt.io

docs.kinetica.com

www.sqlite.org/docs.html

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Firebolt Analytics Inc.

Hypertable Inc.

Kinetica

Dwayne Richard Hipp

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2020

2009

2012

2000

1998

Current release

0.9.8.11, March 2016

7.1, August 2021

3.46.1 (13 August 2024), August 2024

Release 22.1

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Public Domain

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.

Implementation language

C++

C, C++

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux

server-less

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

schema-free

yes

dynamic column types

yes

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

yes

APIs and other access methods

.Net
ODBC
RESTful HTTP API

C++ API
Thrift

JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

Go
JavaScript (Node.js)
Python

C++
Java
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
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++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

user defined functions

PL/SQL

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

selectable replication factor on file system level

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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