DBMS > Datomic vs. Hypertable vs. IRONdb vs. Manticore Search vs. RocksDB

System Properties Comparison Datomic vs. Hypertable vs. IRONdb vs. Manticore Search vs. RocksDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

An open source BigTable implementation based on distributed file systems such as Hadoop

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Multi-storage database for search, including full-text search.

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

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

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

Website

www.datomic.com

www.circonus.com/solutions/time-series-database/

manticoresearch.com

rocksdb.org

Technical documentation

docs.datomic.com

docs.circonus.com/irondb/category/getting-started

manual.manticoresearch.com

github.com/facebook/rocksdb/wiki

Developer

Cognitect

Hypertable Inc.

Circonus LLC.

Manticore Software

Facebook, Inc.

Initial release

2012

2009

2017

2013

Current release

1.0.6735, June 2023

0.9.8.11, March 2016

V0.10.20, January 2018

6.0, February 2023

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

GNU version 3. Commercial license available

commercial

Open Source

GPL version 2

Open Source

BSD

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, Clojure

C++

C and C++

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux

FreeBSD
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like query language

APIs and other access methods

RESTful HTTP API

C++ API
Thrift

HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

C++ API
Java API

Supported programming languages

Clojure
Java

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, in Lua

user defined functions

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Automatic, metric affinity per node

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

selectable replication factor on file system level

configurable replication factor, datacenter aware

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

The original contents of fields are not stored in the Manticore index.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

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