DBMS > Apache Impala vs. Graph Engine vs. H2 vs. SQLite vs. TDengine

System Properties Comparison Apache Impala vs. Graph Engine vs. H2 vs. SQLite vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Widely used embeddable, in-process RDBMS

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Spatial DBMS

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

github.com/taosdata/TDengine
tdengine.com

Technical documentation

impala.apache.org/impala-docs.html

www.graphengine.io/docs/manual

www.h2database.com/html/main.html

www.sqlite.org/docs.html

docs.tdengine.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

Thomas Mueller

Dwayne Richard Hipp

TDEngine, previously Taos Data

Initial release

2013

2010

2005

2000

2019

Current release

4.1.0, June 2022

2.2.220, July 2023

3.45.3 (15 April 2024), April 2024

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Public Domain

Open Source

AGPL V3, also commercial editions available

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

C++

.NET and C

Java

Server operating systems

Linux

.NET

All OS with a Java VM

server-less

Linux
Windows

Data scheme

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

Java

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++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

With clustering: 2 database servers on different computers operate on identical copies of a database

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

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

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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 rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

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7 May 2024

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6 May 2024

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19 April 2024

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15 April 2024

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8 April 2024

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