DBMS > EJDB vs. Faircom EDGE vs. Redis vs. TimescaleDB vs. Titan
System Properties Comparison EJDB vs. Faircom EDGE vs. Redis vs. TimescaleDB vs. Titan
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | EJDB Xexclude from comparison | Faircom EDGE formerly c-treeEDGE Xexclude from comparison | Redis Xexclude from comparison | TimescaleDB Xexclude from comparison | Titan Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Embeddable document-store database library with JSON representation of queries (in MongoDB style) | FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments | Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies. | A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL | Titan is a Graph DBMS optimized for distributed clusters. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store | Key-value store Relational DBMS | Key-value store Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence | Time Series DBMS | Graph DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store with RedisJSON Graph DBMS with RedisGraph Spatial DBMS Search engine with RediSearch Time Series DBMS with RedisTimeSeries Vector DBMS | Relational DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | github.com/Softmotions/ejdb | www.faircom.com/products/faircom-edge | redis.com redis.io | www.timescale.com | github.com/thinkaurelius/titan | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | github.com/Softmotions/ejdb/blob/master/README.md | docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html | docs.redis.com/latest/index.html redis.io/docs | docs.timescale.com | github.com/thinkaurelius/titan/wiki | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Softmotions | FairCom Corporation | Redis project core team, inspired by Salvatore Sanfilippo Development sponsored by Redis Inc. | Timescale | Aurelius, owned by DataStax | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 1979 | 2009 | 2017 | 2012 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | V3, October 2020 | 7.2.4, January 2024 | 2.15.0, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source GPLv2 | commercial Restricted, free version available | Open Source source-available extensions (modules), commercial licenses for Redis Enterprise | Open Source Apache 2.0 | Open Source Apache license, version 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C | ANSI C, C++ | C | C | Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | server-less | Android Linux ARM, x86 Raspbian Windows | BSD Linux OS X Windows ported and maintained by Microsoft Open Technologies, Inc. | Linux OS X Windows | Linux OS X Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | Flexible Schema (defined schema, partial schema, schema free) | schema-free | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes string, integer, double, bool, date, object_id | yes, ANSI Standard SQL Types | partial Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes | numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types | 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 | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | yes with RediSearch module | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | yes ANSI SQL queries | with RediSQL module | yes full PostgreSQL SQL syntax | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | in-process shared library | ADO.NET Direct SQL IoT Microservice layer JDBC MQTT (Message Queue Telemetry Transport) ODBC RESTful HTTP API | proprietary protocol RESP - REdis Serialization Protocol | ADO.NET JDBC native C library ODBC streaming API for large objects | Java API TinkerPop Blueprints TinkerPop Frames TinkerPop Gremlin TinkerPop Rexster | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Actionscript C C# C++ Go Java JavaScript (Node.js) Lua Objective-C Pike Python Ruby | C C# C++ Java JavaScript PHP Python VB.Net | C C# C++ Clojure Crystal D Dart Elixir Erlang Fancy Go Haskell Haxe Java JavaScript (Node.js) Lisp Lua MatLab Objective-C OCaml Pascal Perl PHP Prolog Pure Data Python R Rebol Ruby Rust Scala Scheme Smalltalk Swift Tcl Visual Basic | .Net C C++ Delphi Java JDBC JavaScript Perl PHP Python R Ruby Scheme Tcl | Clojure Java Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | yes .Net, JavaScript, C/C++ | Lua; Redis Functions coming in Redis 7 (slides and Github) | user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | publish/subscribe channels provide some trigger functionality; RedisGears | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | File partitioning Customizable business rules for partitioning | Sharding Automatic hash-based sharding with support for hash-tags for manual sharding | yes, across time and space (hash partitioning) attributes | yes via pluggable storage backends | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | none | yes Synchronous and asynchronous realtime replication based on transaction logs | Multi-source replication with Redis Enterprise Pack Source-replica replication Chained replication is supported | Source-replica replication with hot standby and reads on replicas | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | through RedisGears | no | yes via Faunus, a graph analytics engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency Tunable Consistency | Eventual Consistency Causal consistency can be enabled in Active-Active databases Strong consistency with Redis Raft Strong eventual consistency with Active-Active | Immediate Consistency | Eventual Consistency Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no typically not needed, however similar functionality with collection joins possible | yes when using SQL | no | yes | yes Relationships in graph | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | Atomic execution of command blocks and scripts and optimistic locking | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes Read/Write Locking | yes across SQL and NoSQL | yes Data access is serialized by the server | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes Configurable mechanisms for persistency via snapshots and/or operations logs | yes | yes Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | no | Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL. | Access Control Lists (ACLs): redis.io/docs/management/security/acl LDAP and Role-Based Access Control (RBAC) for Redis Enterprise Mutual TLS authentication: redis.io/docs/management/security/encryption Password-based authentication | fine grained access rights according to SQL-standard | User authentification and security via Rexster Graph Server | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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EJDB | Faircom EDGE formerly c-treeEDGE | Redis | TimescaleDB | Titan | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2018 MySQL, PostgreSQL and Redis are the winners of the March ranking MongoDB is the DBMS of the year, defending the title from last year | Graph DBMS increased their popularity by 500% within the last 2 years Graph DBMSs are gaining in popularity faster than any other database category Innovative Software and Giant Lego Sets, Why FairCom Edge Booth is a Must-Visit at Automate FairCom kicks off new era of database technology USA - English Winners of the 2021 IoT Evolution Product of the Year Awards Announced Trend-Setting Products in Data and Information Management for 2023 How To Collect, Store, and Query IoT Data With MQTT + SQL provided by Google News Cloud firm Redis Labs valued at $2 billion as SoftBank, Tiger Global invest Redis acquires storage engine startup Speedb to enhance its open-source database Boosting throughput for cloud databases Redis moves to source-available licenses Redis expands data management capabilities with Speedb acquisition – Blocks and Files provided by Google News TimescaleDB Is a Vector Database Now, Too Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud provided by Google News Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services Beyond Titan: The Evolution of DataStax's New Graph Database DataStax acquires Aurelius, the startup behind the Titan graph database 5 Q's with Graph Database Expert Marko Rodriguez – Center for Data Innovation DSE Graph review: Graph database does double duty provided by Google News |
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