DBMS > Faircom DB vs. GreptimeDB vs. SurrealDB

System Properties Comparison Faircom DB vs. GreptimeDB vs. SurrealDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Document store
Graph DBMS

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

www.faircom.com/products/faircom-db

greptime.com

surrealdb.com

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.greptime.com

surrealdb.com/docs

Developer

FairCom Corporation

Greptime Inc.

SurrealDB Ltd

Initial release

1979

2022

Current release

V12, November 2020

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2.0

Open Source

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

ANSI C, C++

Rust

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
macOS
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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

yes, ANSI SQL with proprietary extensions

yes

SQL-like query language

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

gRPC
HTTP API
JDBC

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C++
Erlang
Go
Java
JavaScript

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

Simple rights management via user accounts

yes, based on authentication and database rules

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

FairCom Unveils New Look, FairCom DB v13: Introducing 'DB Made Simple'
4 June 2024, Yahoo Finance

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

provided by Google News

SurrealDB is helping developers consolidate their databases
18 June 2024, TechCrunch

SurrealDB Raises $20M To Disrupt Big Data Industry
21 June 2024, Datanami

Multi-model database startup SurrealDB raises $20M and announces cloud beta access
18 June 2024, SiliconANGLE News

SurrealDB Raises $20 Million to Disrupt Database Tech; Introduces New Cloud Beta Access
18 June 2024, PR Newswire

SurrealDB Raises $20M in Funding
18 June 2024, FinSMEs

provided by Google News

Share this page