DBMS > IBM Db2 Event Store vs. SQLite vs. STSdb vs. Teradata Aster vs. TigerGraph

System Properties Comparison IBM Db2 Event Store vs. SQLite vs. STSdb vs. Teradata Aster vs. TigerGraph

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Distributed Event Store optimized for Internet of Things use cases

Widely used embeddable, in-process RDBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Platform for big data analytics on multistructured data sources and types

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

Primary database model

Event Store
Time Series DBMS

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.ibm.com/products/db2-event-store

www.sqlite.org

github.com/STSSoft/STSdb4

www.tigergraph.com

Technical documentation

www.ibm.com/docs/en/db2-event-store

www.sqlite.org/docs.html

docs.tigergraph.com

Developer

IBM

Dwayne Richard Hipp

STS Soft SC

Teradata

Initial release

2017

2000

2011

2005

2017

Current release

2.0

3.45.3 (15 April 2024), April 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Public Domain

Open Source

GPLv2, commercial license available

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

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

server-less

Windows

Linux

Data scheme

yes

dynamic column types

yes

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes

primitive types and user defined types (classes)

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL-92 is not fully supported

yes

SQL-like query language (GSQL)

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.NET Client API

ADO.NET
JDBC
ODBC
OLE DB

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

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C#
Java

C
C#
C++
Java
Python
R

C++
Java

Server-side scripts

Stored procedures

yes

R packages

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

via file-system locks

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

Role-based access control

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