DBMS > BoltDB vs. Ignite vs. PostGIS vs. Snowflake vs. TDengine

System Properties Comparison BoltDB vs. Ignite vs. PostGIS vs. Snowflake vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Spatial extension of PostgreSQL

Cloud-based data warehousing service for structured and semi-structured data

Time Series DBMS and big data platform

Primary database model

Key-value store

Key-value store
Relational DBMS

Spatial DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

github.com/boltdb/bolt

ignite.apache.org

postgis.net

www.snowflake.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

apacheignite.readme.io/docs

postgis.net/documentation

docs.snowflake.net/manuals/index.html

docs.tdengine.com

Developer

Apache Software Foundation

Snowflake Computing Inc.

TDEngine, previously Taos Data

Initial release

2013

2015

2005

2014

2019

Current release

Apache Ignite 2.6

3.4.2, February 2024

3.0, August 2022

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

GPL v2.0

commercial

Open Source

AGPL V3, also commercial editions available

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++, Java, .Net

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

hosted

Linux
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes (cache interceptors and events)

yes

similar concept for controling cloud resources

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

based on PostgreSQL

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

yes

based on PostgreSQL

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

User concepts

Access control

Security Hooks for custom implementations

yes

based on PostgreSQL

Users with fine-grained authorization concept, user roles and pluggable authentication

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...
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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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6 June 2024

Comprehensive Comparison Between TDengine and TimescaleDB
5 June 2024

Mastering Memory Leak Detection in TDengine
31 May 2024

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

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