DBMS > Alibaba Cloud TSDB vs. AnzoGraph DB vs. HEAVY.AI vs. LeanXcale

System Properties Comparison Alibaba Cloud TSDB vs. AnzoGraph DB vs. HEAVY.AI vs. LeanXcale

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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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Time Series DBMS

Graph DBMS
RDF store

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#301	Overall
	#26	Time Series DBMS

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

cambridgesemantics.com/anzograph

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

www.leanxcale.com

Technical documentation

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

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.heavy.ai

Developer

Alibaba

Cambridge Semantics

HEAVY.AI, Inc.

LeanXcale

Initial release

2018

2016

2015

Current release

2.3, January 2021

5.10, January 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2; enterprise edition available

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

C++ and CUDA

Server operating systems

hosted

Linux

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

Numeric data and Strings

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

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

through Apache Derby

APIs and other access methods

HTTP REST

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC
Thrift
Vega

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Java

C++
Java
Python

All languages supporting JDBC/ODBC/Thrift
Python

C
Java
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

In-memory capabilities

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

yes

User concepts

Access control

Access managed on TSDB instance level

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

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