DBMS > GreptimeDB vs. LevelDB vs. ObjectBox vs. Snowflake vs. Teradata Aster

System Properties Comparison GreptimeDB vs. LevelDB vs. ObjectBox vs. Snowflake vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Extremely fast embedded database for small devices, IoT and Mobile

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

greptime.com

github.com/google/leveldb

objectbox.io

www.snowflake.com

Technical documentation

docs.greptime.com

github.com/google/leveldb/blob/main/doc/index.md

docs.objectbox.io

docs.snowflake.net/manuals/index.html

Developer

Greptime Inc.

Google

ObjectBox Limited

Snowflake Computing Inc.

Teradata

Initial release

2022

2011

2017

2014

2005

Current release

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Apache License 2.0

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

Rust

C++

C and C++

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Illumos
Linux
OS X
Windows

Android
iOS
Linux
macOS
Windows

hosted

Linux

Data scheme

schema-free, schema definition possible

schema-free

yes

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

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
HTTP API
JDBC

Proprietary native API

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C++
Erlang
Go
Java
JavaScript

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

Python

user defined functions

R packages

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

online/offline synchronization between client and server

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

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

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

User concepts

Access control

Simple rights management via user accounts

yes

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

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

News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.