DBMS > atoti vs. Axibase vs. Databricks vs. RocksDB

System Properties Comparison atoti vs. Axibase vs. Databricks vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Object oriented DBMS

Time Series DBMS

Document store
Relational DBMS

Key-value store

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

atoti.io

axibase.com/docs/atsd/finance

www.databricks.com

rocksdb.org

Technical documentation

docs.atoti.io

docs.databricks.com

github.com/facebook/rocksdb/wiki

Developer

ActiveViam

Axibase Corporation

Databricks

Facebook, Inc.

Initial release

2013

Current release

15585

8.11.4, April 2024

License

Commercial or Open Source

commercial

free versions available

commercial

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

commercial

Open Source

BSD

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++

Server operating systems

Linux

hosted

Linux

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, 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.

yes

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

with Databricks SQL

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Python
R
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Python

yes

user defined functions and aggregates

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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