DBMS > Alibaba Cloud Table Store vs. Hyprcubd vs. Microsoft Azure Cosmos DB vs. ScyllaDB vs. Warp 10

System Properties Comparison Alibaba Cloud Table Store vs. Hyprcubd vs. Microsoft Azure Cosmos DB vs. ScyllaDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Serverless Time Series DBMS

Globally distributed, horizontally scalable, multi-model database service

Cassandra and DynamoDB compatible wide column store

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Wide column store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

Key-value store

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

hyprcubd.com (offline)

azure.microsoft.com/services/cosmos-db

www.scylladb.com

www.warp10.io

Technical documentation

www.alibabacloud.com/help/en/tablestore

learn.microsoft.com/azure/cosmos-db

docs.scylladb.com

www.warp10.io/content/02_Getting_started

Developer

Alibaba

Hyprcubd, Inc.

Microsoft

ScyllaDB

SenX

Initial release

2016

2014

2015

Current release

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Open Source (AGPL), commercial license available

Open Source

Apache License 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.

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Implementation language

C++

Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

JSON types

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

All properties auto-indexed by default

yes

cluster global secondary indices

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements (CQL)

APIs and other access methods

HTTP API

gRPC (https)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

HTTP API
Jupyter
WebSocket

Supported programming languages

Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

JavaScript

yes, Lua

yes

WarpScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

selectable replication factor

Representation of geographical distribution of servers is possible

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

Multi-item ACID transactions with snapshot isolation within a partition

Atomicity and isolation are supported for single operations

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

in-memory tables

yes

User concepts

Access control

Access rights based on subaccounts and tokens

token access

Access rights can be defined down to the item level

Access rights for users can be defined per object

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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