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DBMS > Faircom DB vs. PostgreSQL vs. Redis vs. Splice Machine vs. Tarantool

System Properties Comparison Faircom DB vs. PostgreSQL vs. Redis vs. Splice Machine vs. Tarantool

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonPostgreSQL  Xexclude from comparisonRedis  Xexclude from comparisonSplice Machine  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLPopular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments infoRedis focuses on performance so most of its design decisions prioritize high performance and very low latencies.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelKey-value store
Relational DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Key-value store infoMultiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistenceRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Document store infowith RedisJSON
Graph DBMS infowith RedisGraph
Spatial DBMS
Search engine infowith RediSearch
Time Series DBMS infowith RedisTimeSeries
Vector DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score155.94
Rank#6  Overall
#1  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbwww.postgresql.orgredis.com
redis.io
splicemachine.comwww.tarantool.io
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.postgresql.org/­docsdocs.redis.com/­latest/­index.html
redis.io/­docs
splicemachine.com/­how-it-workswww.tarantool.io/­en/­doc
DeveloperFairCom CorporationPostgreSQL Global Development Group infowww.postgresql.org/­developerRedis project core team, inspired by Salvatore Sanfilippo infoDevelopment sponsored by Redis Inc.Splice MachineVK
Initial release19791989 info1989: Postgres, 1996: PostgreSQL200920142008
Current releaseV12, November 202016.3, May 20247.2.5, May 20243.1, March 20212.10.0, May 2022
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoBSDOpen Source infosource-available extensions (modules), commercial licenses for Redis EnterpriseOpen Source infoAGPL 3.0, commercial license availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++CCJavaC and C++
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
BSD
Linux
OS X
Windows infoported and maintained by Microsoft Open Technologies, Inc.
Linux
OS X
Solaris
Windows
BSD
Linux
macOS
Data schemeschema free, schema optional, schema required, partial schema,yesschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyes infowith RediSearch moduleyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsyes infostandard with numerous extensionswith RediSQL moduleyesFull-featured ANSI SQL support
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
proprietary protocol infoRESP - REdis Serialization ProtocolJDBC
Native Spark Datasource
ODBC
Open binary protocol
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Lua; Redis Functions coming in Redis 7 (slides and Github)yes infoJavaLua, C and SQL stored procedures
Triggersyesyespublish/subscribe channels provide some trigger functionality; RedisGearsyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningpartitioning by range, list and (since PostgreSQL 11) by hashSharding infoAutomatic hash-based sharding with support for hash-tags for manual shardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication infowith Redis Enterprise Pack
Source-replica replication infoChained replication is supported
Multi-source replication
Source-replica replication
Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonothrough RedisGearsYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active
Immediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACIDAtomic execution of command blocks and scripts and optimistic lockingACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoData access is serialized by the serveryes, multi-version concurrency control (MVCC)yes, cooperative multitasking
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standardAccess 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
Access rights for users, groups and roles according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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