DBMS > Atos Standard Common Repository vs. Axibase vs. CrateDB vs. JaguarDB

System Properties Comparison Atos Standard Common Repository vs. Axibase vs. CrateDB vs. JaguarDB

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Distributed Database based on Lucene

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Document store
Key-value store

Time Series DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Key-value store
Vector DBMS

Secondary database models

Relational DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

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

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

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

axibase.com/docs/atsd/finance

cratedb.com

www.jaguardb.com

Technical documentation

cratedb.com/docs

www.jaguardb.com/support.html

Developer

Atos Convergence Creators

Axibase Corporation

Crate

DataJaguar, Inc.

Initial release

2016

2013

2015

Current release

1703

15585

5.8.1, August 2024

3.3 July 2023

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

the server part. Clients available in other languages

Server operating systems

Linux

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

Data scheme

Schema and schema-less with LDAP views

yes

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

yes

Typing

predefined data types such as float or date

optional

yes

short, integer, long, float, double, decimal, string

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes, but no triggers and constraints, and PostgreSQL compatibility

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

LDAP

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Go
Java
PHP
Python
R
Ruby

.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

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

Server-side scripts

Stored procedures

yes

user defined functions (Javascript)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Configurable replication on table/partition-level

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 or Eventual Consistency depending on configuration

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

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

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

LDAP bind authentication

rights management via user accounts

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