DBMS > Datomic vs. LevelDB vs. TigerGraph vs. TimesTen

System Properties Comparison Datomic vs. LevelDB vs. TigerGraph vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.datomic.com

github.com/google/leveldb

www.tigergraph.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.datomic.com

github.com/google/leveldb/blob/main/doc/index.md

docs.tigergraph.com

docs.oracle.com/database/timesten-18.1

Developer

Cognitect

Google

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2011

2017

1998

Current release

1.0.6735, June 2023

1.23, February 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

commercial

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++

Server operating systems

All OS with a Java VM

Illumos
Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language (GSQL)

yes

APIs and other access methods

RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Clojure
Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

PL/SQL

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Multi-source replication
Source-replica replication

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 or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

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

with automatic compression on writes

yes

by means of logfiles and checkpoints

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

Role-based access control

fine grained access rights according to SQL-standard

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