DBMS > ITTIA vs. Postgres-XL vs. RocksDB vs. Warp 10

System Properties Comparison ITTIA vs. Postgres-XL vs. RocksDB vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Edge Time Series DBMS with Real-Time Stream Processing

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

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

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

Technical documentation

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

www.warp10.io/content/02_Getting_started

Developer

ITTIA L.L.C.

Facebook, Inc.

SenX

Initial release

2007

2014

since 2012, originally named StormDB

2013

2015

Current release

8.7

10 R1, October 2018

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

BSD

Open Source

Apache License 2.0

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

C and C++

C++

Java

Server operating systems

Linux
Windows

Linux
macOS

Linux

Linux
OS X
Windows

Data scheme

Fixed schema

yes

schema-free

Typing

predefined data types such as float or date

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC
RESTful HTTP API
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

C++ API
Java API

HTTP API
Jupyter
WebSocket

Supported programming languages

C
C++
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

MVCC

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

Database file passwords

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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