DBMS > Alibaba Cloud Table Store vs. CrateDB vs. EsgynDB vs. InfinityDB vs. JaguarDB

System Properties Comparison Alibaba Cloud Table Store vs. CrateDB vs. EsgynDB vs. InfinityDB vs. JaguarDB

Editorial information provided by DB-Engines

Name

Description

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

Distributed Database based on Lucene

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A Java embedded Key-Value Store which extends the Java Map interface

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Wide column store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Key-value store

Key-value store
Vector DBMS

Secondary database models

Relational DBMS

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

Score	0.25
Rank	#294	Overall
	#12	Wide column stores

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Website

www.alibabacloud.com/product/table-store

Technical documentation

www.alibabacloud.com/help/en/tablestore

cratedb.com/docs

boilerbay.com/infinitydb/manual

www.jaguardb.com/support.html

Developer

Alibaba

Crate

Esgyn

Boiler Bay Inc.

DataJaguar, Inc.

Initial release

2016

2013

2015

2002

2015

Current release

5.8.1, August 2024

4.0

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

GPL V3.0

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

Java

C++, Java

Java

C++

the server part. Clients available in other languages

Server operating systems

hosted

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

All OS with a Java VM

Linux

Data scheme

schema-free

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

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

ADO.NET
JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
ODBC

Supported programming languages

Java
Python

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

All languages supporting JDBC/ODBC/ADO.Net

Java

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions (Javascript)

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Configurable replication on table/partition-level

Multi-source replication between multi datacenters

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

Atomic single-row operations

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Optimistic locking for transactions; no isolation for bulk loads

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.

User concepts

Access control

Access rights based on subaccounts and tokens

rights management via user accounts

fine grained access rights according to SQL-standard

rights management via user accounts

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