DBMS > GreptimeDB vs. HugeGraph vs. Sadas Engine vs. TimesTen

System Properties Comparison GreptimeDB vs. HugeGraph vs. Sadas Engine vs. TimesTen

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

In-Memory RDBMS compatible to Oracle

Primary database model

Time Series DBMS

Graph DBMS

Relational DBMS

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

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

greptime.com

github.com/hugegraph
hugegraph.apache.org

www.sadasengine.com

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

Technical documentation

docs.greptime.com

hugegraph.apache.org/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.oracle.com/database/timesten-18.1

Developer

Greptime Inc.

Baidu

SADAS s.r.l.

Oracle, TimesTen Performance Software, HP

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

Initial release

2022

2018

2006

1998

Current release

0.9

8.0

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

free trial version available

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

Rust

Java

C++

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
macOS
Unix

AIX
Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free, schema definition possible

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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
HTTP API
JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Erlang
Go
Java
JavaScript

Groovy
Java
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Python

asynchronous Gremlin script jobs

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Simple rights management via user accounts

Users, roles and permissions

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

Share this page