DBMS > Alibaba Cloud TSDB vs. HEAVY.AI vs. Lovefield vs. NSDb

System Properties Comparison Alibaba Cloud TSDB vs. HEAVY.AI vs. Lovefield vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

A stable, reliable, and cost-effective online high-performance time series database service

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.24
Rank	#312	Overall
	#27	Time Series DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Website

www.alibabacloud.com/product/hitsdb

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

nsdb.io

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

docs.heavy.ai

github.com/google/lovefield/blob/master/docs/spec_index.md

nsdb.io/Architecture

Developer

Alibaba

HEAVY.AI, Inc.

Google

Initial release

2016

2014

2017

Current release

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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++ and CUDA

JavaScript

Java, Scala

Server operating systems

hosted

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numeric data and Strings

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

HTTP REST

JDBC
ODBC
Thrift
Vega

gRPC
HTTP REST
WebSocket

Supported programming languages

Java

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Java
Scala

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

Using Apache Lucene

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access managed on TSDB instance level

fine grained access rights according to SQL-standard

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